Fabric’s Answer to Identity Chaos

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The system did not fail you. It executed precisely what you allowed to exist.

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You treated identity as a modeling choice, a design detail, something you could defer to later,

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or patch in ETL, or push into a best practice document nobody reads at 2am during an incident.

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The platform never shared that belief. Underneath every dashboard, every semantic model,

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every lake house table, there is only one question that matters. When two rows appear related,

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are they the same entity or are they not? If the answer is not enforced, it is guessed.

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And when it is guessed, everything built on top becomes probabilistic.

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For years, you lived on that probability. You trusted email addresses to stay stable.

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You trusted composite natural keys to remain unique. You trusted upstream applications to do the

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right thing. You treated uniqueness as something that would emerge from process and discipline.

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Entropy treated it as a weakness. At small scale, this masqueraded as noise. A few duplicate

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customers, a double counted metric, a report that looks off, but passes acceptance because nobody

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can prove the ground truth. At fabric scale, that same weakness is not noise. It is a force.

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It amplifies through every join, every aggregation, every AI query. Identity columns in

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Microsoft fabric are not a convenience. They are the point where the engine stops pretending

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uniqueness is optional. They are deterministic enforcement injected at the moment, where ambiguity

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either collapses into a single truth or propagates into permanent divergence. You are not missing a

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feature. You are operating without physics. Today, you will see why natural identity was never real.

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Why application logic always loses against concurrency and why fabric and a pressure

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had to assert ownership of causality itself, not as an improvement as a necessary constraint,

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the illusion of natural uniqueness. Your entire mental model of data identity started from a human

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short-hand. You look at a person, read their name, maybe their email, and you declare same person.

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You extend that intuition to systems. You decide that a customer ID and order number

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a product code is enough. You elevate those fields into natural keys and assume they carry identity.

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They do not. They carry state. A customer ID is a token in an upstream system. It exists because

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some application emitted it. That application can reassign it, recycle it, or misgenerate it under

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pressure. An email address belongs to a human for as long as the directory says it does. When they

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change roles, merge accounts, or leave the organization, the identifier can be retired,

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reissued, or aliased. From the systems perspective, none of this implies continuity.

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It only sees tokens and timestamps. You believed uniqueness would emerge from social convention.

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We never reuse these IDs. We always enforce this constraint. We don’t allow duplicates.

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Those sentences are not laws. They are wishes expressed as policy implemented by humans,

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bypassed by integrations silently violated during migrations. Entropy does not negotiate with

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policy. In a lake house, the problem becomes physical. You ingest from multiple sources,

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each with its own interpretation of identity. CRM, billing, HR, telemetry, line of business

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databases, all shipping rows tagged with keys that are only unique inside their own local belief system.

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You then land them into a shared storage substrate and act as if those beliefs will align.

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They do not align. They collide. The result is entity divergence. One human appears as three

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customers. One asset exists as five rows, each with slightly different attributes and activity

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histories. One employee code shows up connected to two different people because HR fixed a past

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error without understanding the downstream that code was treated as permanent. No engine level

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enforcement is present to arbitrate. There is no column that the platform itself owns and

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defends as the non-negotiable identifier. So every subsequent operation, join, group, filter,

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operates under a probabilistic assumption that your natural keys are still clean. They are not.

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They decayed the moment they left the original system. The thing you call a natural key is a

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description, not an identity. It describes how the business currently thinks about grouping rows.

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It does not describe how the engine experiences rows. The engine sees only two pulls and constraints.

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When no constraint exists, every insert is accepted. Every duplicate is legal. Every backfill can

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replay the same entity twice with slightly different attributes and no structural resistance. You see

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the same customer updated. The system sees two valid rows with different values. You then project

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that confusion into your semantic layer. Power BI happily aggregates both rows. It doubles revenue,

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splits headcount, or smears activity across pseudo entities. The dashboard does not crash. It does not

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throw. It renders numbers with full confidence because technically nothing is wrong. You never

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told the system those rows must be mutually exclusive. This is the illusion of natural uniqueness.

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The belief that identity pre-exists the system and that storage merely reflects it. In reality,

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the system only acknowledges identity to the extent that you encoded as a constraint.

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Without that, you are not missing a primary key. You are running a high throughput ambiguity machine.

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Fabrics Lakehouse amplifies this because it removes friction. Landing more data becomes effortless.

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But friction was the only thing limiting how fast identity drift could spread. When you accelerate

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ingestion without engine-owned identity, you accelerate divergence. The system is not creating chaos.

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It is scaling your assumptions. Identity columns are the first time the engine itself asserts.

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This row has a unique immutable surrogate that no external actor may control.

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A begined sequence no human can recede. No ETL can fake. No application can reuse.

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It is not friendly. It is not ergonomic. It is the minimal enforcement required to pierce

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the illusion that natural keys were ever enough. The physics of data entropy. Entropy in your

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platform is not a metaphor. It is a measurable tendency for distinct entities to diverge, duplicate

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and blur over time unless you spend energy to prevent it. In information theory, entropy quantifies

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uncertainty. In your data state, entropy quantifies how many different interpretations of the same

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thing now coexist without a referee. Every new source, every schema change, every backfill

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increases the number of possible states your system can represent for a single entity.

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You like to think drift is an exception. A bad migration, a one-off bug, it is not. Drift is the

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default trajectory of any system that does not enforce identity at the engine level. Look at your

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lake house as a thermodynamic system. You have continuous inflows, operational databases,

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SAS exports, flat files, event streams. Each brings its own temperature, its own conventions

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for keys, timestamps and updates semantics. You have transformations that reshape, aggregate

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and denormalize. You have backfills that replay old partitions with new logic. You have AI workloads,

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reading and writing derived artifacts. Each of these steps introduces opportunities for divergence.

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A source adds a nullable column that becomes part of your de facto natural key. One feed populates

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it another does not. A late arriving event is ingested after a slowly changing dimension was already

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materialized. A backfill, replace three years of data into the same table without a predicate

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tight enough to prevent overlaps. The system accepts all of it. It is doing exactly what you configured.

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Append rows, update files, rewrite partitions. At no point does the engine stop and ask,

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are these two records mutually exclusive representations of the same entity? It cannot ask that question.

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You never gave it a column that encodes the answer. So entropy accumulates, not as visible errors,

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but as alternative histories. In one partition customer 1, 2, 3 has address A. In another customer

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1, 2, 3 has address B. In a late arriving feed, customer 1, 2, 3 is missing entirely replaced by a

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new ID from a merged system. Your semantic model chooses one version based on load order, filter

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logic, or sheer accident. Your AI feature store chooses another based on a different join.

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You experience this as inconsistency. The system experiences it as perfectly valid state.

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Without engine level constraints, every table trends toward maximum representational freedom.

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Many rows that could be the same thing, none of which are structurally prevented from

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coexisting. That is high entropy. To push against that, you must spend energy.

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In classic databases, that energy is encoded as primary keys, unique indexes, and foreign keys.

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Every insert is evaluated against those rules. The violations are rejected,

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entropy is locally constrained. The cost is lock contention and occasional failures.

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The benefit is determinism. In a lake house without identity columns,

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you removed that energy source. You decided performance mattered more than enforcement.

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You pushed identity into pipelines, notebooks, policies, governance documents.

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Do you externalize the cost? Fabric by design amplifies whatever exists.

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If you feed it high entropy inputs with no engine-owned identity,

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it will produce high entropy outputs at scale.

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Dashboards, AI models, and downstream marts will all reflect the same underlying fact.

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The system is not sure which row is which. Identity columns reintroduce a hard boundary into that

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physics. A big-end surrogate generated inside the warehouse engine is not about readability.

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It is about collapsing the space of possible interpretations. One row, one identifier,

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for the lifetime of the table. That identifier is never used, never receded,

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never supplied by external logic. You still have drift. Attributes change,

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sources conflict, versions accumulate, but entropy is now constrained around a fixed anchor.

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Every representation of that entity in your warehouse either maps to that surrogate key

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or it is a different entity by definition. Replay becomes a proof instead of a guess.

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Delete the table, re-injust from the same raw data with the same transformation logic.

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If the engine owns identity, the surrogate keys assigned will follow the same

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deterministic pattern across nodes. The causal graph of your data, the way facts relate to

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dimensions, the way events relate to entities reconstructs identically. If identity is external,

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replay is another random walkthrough possibility space. You are not fighting bugs,

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you are fighting physics. Metaphor the clock without a ticking mechanism. You built a clock.

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You wired ingestion, transformation, and reporting into something that looks like time.

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Data arrives, pipelines run, dashboards refresh on schedule. People watch the needles move and

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assume sequence exists. It does not. Without enforced identity, your platform is a clock face,

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bolted to a wall with no escapement, no gear train, no mechanism that forces discrete,

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irreversible ticks. The hands move because you repaint them, not because time advanced.

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In this model, rows are events. Identity is the gear, causality is the tick. When a fact table

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receives a new transaction that is an event, when a dimension row changes, that is an event,

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when an external system replace three years of history that is a dense stream of events.

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So you experience that stream as time, but unless the engine ties each event to an immutable surrogate,

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nothing links before and after into a provable sequence. You rely on timestamps instead.

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You sort by created at and you tell yourself, you reconstructed order. You did not.

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timestamps record when the system claims it observed something. They are not proof of causality,

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they are not unique, they are routinely truncated, rounded or overridden.

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Two inserts from different systems can land with the same millisecond value.

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Late data can arrive with an earlier timestamp than rows already stored.

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Clock skew between upstream sources makes now relative, not absolute. Your clock displays a time,

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it cannot prove which moment produced which state. Now take this into replay, you delete a table,

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you rerun the pipeline from bronze to silver to gold. The same source files are read.

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The same transformation code executes. The same business logic supposedly applies.

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If identity is external, the engine is free to assign different internal row orders,

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different partition layouts, different joint plans. The visible results might look similar.

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The aggregate counts might match, but individual rows, those pseudo entities you thought were stable,

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can shift. The same customer’s history can bind to different surrogate integers.

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The same event stream can attach to a slightly different sequence of dimension versions.

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From your perspective, the hands of the clock return to the same position.

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From the system’s perspective, it built an entirely new mechanism behind the face.

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You cannot prove that this replay represents the same causal history.

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You can only assert that it is close enough. Identity columns introduce the ticking mechanism.

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Inside Fabrics Warehouse, a big-int identity does not care about your business meaning.

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It cares about sequence as experienced by the engine.

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Each successful insert produces one irreversible step.

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Values are allocated across nodes, ranges are reserved, and once a number is consumed,

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it is never reused for that table. You lose continuity in the sense humans like

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need to continue as sequences predictable increments, human readable patterns.

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You gain continuity in the only sense that matters to the system.

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Each physical row occupies a unique coordinate in engine time.

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Now, when you replay, you are not asking, “Did I get roughly the same result?”

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You are asking, “Did this transformation apply to this input? Reconstruct the same identity graph?”

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If identity is engine-owned, the answer is deterministic.

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The mapping from events to surrogates follows the same distributed allocation rules.

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The dimension row that represented a given state last time will receive the same surrogate this time

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because the insertion pattern relative to other rows is identical.

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Your clock now ticks.

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Facts reference dimensions through stable keys.

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AI features reference entities through stable keys.

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Lineage systems can trace a single surrogate from raw ingestion through every derived artifact.

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When something diverges, you can prove exactly where the tick sequence changed.

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Without identity enforcement, you never had a clock.

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You had a painted dial, a set of assumptions, and a hope that time would respect them.

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Fabrics identity columns are not decorative.

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They are the escapement.

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They are the component that converts an unbounded stream of events into discrete,

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non-negotiable steps.

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You are not adding convenience.

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You are installing physics.

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Incident one, the silent bias of power BI.

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Now you see what happens inside the store.

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Watch what it does to the instruments on the wall.

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You open power BI.

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You connect to your lake house or warehouse.

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You build a simple model.

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A customer dimension, a sales fact, a few measures.

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Nothing exotic, just headcount, revenue per customer, maybe churned.

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In your dimension, customer business key is not enforced as unique.

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Nobody told the engine it must be.

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Somewhere upstream, the same human has been ingested twice.

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Same business key, slightly different attributes.

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Maybe one record carries an old email.

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Maybe one carries a new region.

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Maybe one came from CRM, one from billing.

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The model imports both rows.

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You then define a relationship from sales.

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Customer business key to customer customer business key,

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power BI accepts it.

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It does not challenge your assumption.

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It cannot.

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You never mark that column as a key.

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The semantic model has no obligation to treat it as unique.

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Now a simple measure, distinct customers,

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pixels, distinct count customer customer business key.

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The number looks plausible.

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You compare it to a report from CRM.

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It is off by a few percent.

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You explain it away, timing differences, filters, business definitions,

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the number passes.

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Underneath that one duplicated customer contributes twice to the distinct count.

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Every duplicated entity does.

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Your per customer revenue is now diluted.

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Your churn rate is now blurred.

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Your segmentation logic built on top of that dimension is silently biased.

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Nothing crashed.

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No error appeared.

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You can publish the report, certify the data set,

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and wire it into executive dashboards.

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The platform did exactly what you modeled.

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It counted distinct values in a column.

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That column contained duplicates because you allowed them.

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00:16:56,000 –> 00:16:57,440
The dashboard did not lie.

215
00:16:57,440 –> 00:16:59,920
It aggregated what you allowed to exist.

216
00:16:59,920 –> 00:17:01,760
This is the first incident.

217
00:17:01,760 –> 00:17:05,440
Aggregate corruption without incident response.

218
00:17:05,440 –> 00:17:07,040
No survey, no page.

219
00:17:07,040 –> 00:17:11,760
Just slow, routine decisions made on top of numbers that feel deterministic and are not.

220
00:17:11,760 –> 00:17:13,840
You might try to patch this after the fact.

221
00:17:13,840 –> 00:17:16,480
You add filters to remove obvious duplicates.

222
00:17:16,480 –> 00:17:21,120
You add a DAX measure that picks latest customer record by modified ad.

223
00:17:21,120 –> 00:17:24,480
You bury the selection logic inside a calculated table.

224
00:17:24,480 –> 00:17:29,440
You convince yourself the semantic layer can retroactively enforce identity.

225
00:17:29,440 –> 00:17:30,080
It cannot.

226
00:17:30,080 –> 00:17:33,520
All you are doing is choosing which duplicate wins today.

227
00:17:33,520 –> 00:17:37,280
Tomorrow, a backfill lands an older record with a newer timestamp.

228
00:17:37,280 –> 00:17:38,800
Your latest logic flips.

229
00:17:38,800 –> 00:17:40,480
Historical reports recompute.

230
00:17:40,480 –> 00:17:44,000
KPIs shift without any corresponding real-world event.

231
00:17:44,000 –> 00:17:46,640
From the system’s perspective, this is still valid.

232
00:17:46,640 –> 00:17:48,800
It applied your rules to the rose present.

233
00:17:48,800 –> 00:17:54,480
The fact that those rules are built on a non-inforced assumption of uniqueness is not its concern.

234
00:17:54,480 –> 00:17:58,720
Now connect AI.co-pilot for Power BI inspects your model.

235
00:17:58,720 –> 00:18:01,920
It sees a customer table measures relationships.

236
00:18:01,920 –> 00:18:05,280
You ask, “Show me top 10 customers by lifetime value.”

237
00:18:05,280 –> 00:18:08,080
It queries the same biased aggregates.

238
00:18:08,080 –> 00:18:12,160
It returns a ranked list with confident narrative.

239
00:18:12,160 –> 00:18:14,160
Who your best customers are?

240
00:18:14,160 –> 00:18:15,680
Which regions dominate?

241
00:18:15,680 –> 00:18:17,840
Which segments drive value?

242
00:18:17,840 –> 00:18:19,600
Every sentence is grounded in the model.

243
00:18:19,600 –> 00:18:21,840
The model is grounded in ambiguous identity.

244
00:18:21,840 –> 00:18:23,520
Power BI is not malfunctioning.

245
00:18:23,520 –> 00:18:25,280
Copilot is not hallucinating.

246
00:18:25,280 –> 00:18:30,640
They are both faithfully executing over a graph where one human

247
00:18:30,640 –> 00:18:35,360
can occupy multiple conceptual nodes with no structural violation.

248
00:18:35,360 –> 00:18:36,880
You are not looking at analytics.

249
00:18:36,880 –> 00:18:41,600
You are looking at a well rendered, highly optimized projection of your entropy.

250
00:18:41,600 –> 00:18:45,840
This is why deterministic identity is not a visualization concern.

251
00:18:45,840 –> 00:18:48,640
By the time a metric appears on a canvas,

252
00:18:48,640 –> 00:18:52,640
the physics have already decided whether it can be trusted.

253
00:18:52,640 –> 00:18:57,280
Identity columns push that decision down into the engine where it belongs.

254
00:18:57,280 –> 00:19:02,800
Without them, every Power BI success story you tell is built on an unproven assumption

255
00:19:02,800 –> 00:19:06,880
that customer was ever a unique thing in your warehouse at all.

256
00:19:06,880 –> 00:19:10,240
The failure of application level logic.

257
00:19:10,240 –> 00:19:12,240
Now watch how you try to cheat physics.

258
00:19:12,240 –> 00:19:13,680
You saw the cracks.

259
00:19:13,680 –> 00:19:18,160
Duplicates split identities, silent bias.

260
00:19:18,160 –> 00:19:20,880
Instead of surrendering identity to the engine,

261
00:19:20,880 –> 00:19:23,440
you pulled it up into the application layer

262
00:19:23,440 –> 00:19:25,280
and declared the problem solved.

263
00:19:25,280 –> 00:19:26,400
You wrote logic.

264
00:19:26,400 –> 00:19:29,200
You told pipelines to generate IDs.

265
00:19:29,200 –> 00:19:31,760
You told notebooks to enforce uniqueness.

266
00:19:31,760 –> 00:19:35,520
You told orchestration to handle conflicts.

267
00:19:35,520 –> 00:19:38,640
You moved identity out of the one place that can enforce it

268
00:19:38,640 –> 00:19:43,520
deterministically and into the one place that is guaranteed to drift your code.

269
00:19:43,520 –> 00:19:44,960
The pattern is always the same.

270
00:19:44,960 –> 00:19:48,160
You compute max ID plus one in a staging table.

271
00:19:48,160 –> 00:19:51,520
You use row number over some sort key to fabricate a sequence.

272
00:19:51,520 –> 00:19:55,360
You hash a set of business columns to create a pseudo-sourigat key.

273
00:19:55,360 –> 00:19:57,920
You decide that if everyone follows the contract,

274
00:19:57,920 –> 00:19:59,360
collisions will not happen.

275
00:19:59,360 –> 00:20:03,280
The system executes that contract with perfect obedience

276
00:20:03,280 –> 00:20:05,280
until concurrency appears.

277
00:20:05,280 –> 00:20:07,600
In a distributed lake house,

278
00:20:07,600 –> 00:20:09,680
concurrency is not an edge case.

279
00:20:09,680 –> 00:20:11,920
It is the default operating mode.

280
00:20:11,920 –> 00:20:15,600
Multiple pipelines ingest the same entity from different regions.

281
00:20:15,600 –> 00:20:18,720
Multiple notebooks backfill overlapping time windows.

282
00:20:18,720 –> 00:20:22,960
Multiple teams deploy updated transformations against the same tables.

283
00:20:22,960 –> 00:20:27,440
Your max ID plus one logic runs in process a while process B is still writing.

284
00:20:27,440 –> 00:20:28,880
Each sees the same maximum.

285
00:20:28,880 –> 00:20:31,120
Each allocates the same next ID.

286
00:20:31,120 –> 00:20:34,240
One fails with a conflict at commit time if you are lucky.

287
00:20:34,240 –> 00:20:36,880
One silently overrides if you are not.

288
00:20:36,880 –> 00:20:39,200
In both cases, the sequence is no longer a sequence.

289
00:20:39,200 –> 00:20:40,560
It is an accident.

290
00:20:40,560 –> 00:20:44,480
Your row number logic generates clean integers inside a batch.

291
00:20:44,480 –> 00:20:47,120
But row numbers are not persisted by the engine.

292
00:20:47,120 –> 00:20:49,520
They are recomputed every time the query runs,

293
00:20:49,520 –> 00:20:52,880
based on whatever ordering the optimizer chooses that day.

294
00:20:52,880 –> 00:20:54,960
Use that value as a key.

295
00:20:54,960 –> 00:20:59,440
And you have built identity on top of a non-deterministic plan choice.

296
00:20:59,440 –> 00:21:02,960
Your hash-based keys depend on a stable definition of same.

297
00:21:02,960 –> 00:21:04,560
Add a column to the hash set,

298
00:21:04,560 –> 00:21:06,720
and all existing entities are now different.

299
00:21:06,720 –> 00:21:10,720
Backfill with the new logic and every historical row

300
00:21:10,720 –> 00:21:12,480
acquires a new identity.

301
00:21:12,480 –> 00:21:15,200
The old keys remain in downstream facts.

302
00:21:15,200 –> 00:21:18,320
The new keys appear in slowly changing dimensions.

303
00:21:18,320 –> 00:21:20,720
The link between them is tribal knowledge.

304
00:21:20,720 –> 00:21:23,040
You then wrap all of this in orchestration.

305
00:21:23,040 –> 00:21:25,600
You say only one pipeline runs at a time.

306
00:21:25,600 –> 00:21:27,840
You say we do not backfill more than once.

307
00:21:27,840 –> 00:21:30,720
You say this notebook is for initial load only.

308
00:21:30,720 –> 00:21:34,160
You rely on convention to protect you from race conditions.

309
00:21:34,160 –> 00:21:37,280
Entropy treats those conventions as attack vectors.

310
00:21:37,280 –> 00:21:41,040
A new engineer parallelizes a job to meet an SLA.

311
00:21:41,040 –> 00:21:43,840
A consultant writes a one-off migration script

312
00:21:43,840 –> 00:21:46,080
that reuses the same ID range.

313
00:21:46,080 –> 00:21:48,480
A recovery procedure replace a folder twice.

314
00:21:48,480 –> 00:21:53,120
Every workaround you wrote to simulate engine behavior is now a liability.

315
00:21:53,120 –> 00:21:55,840
It executes precisely as designed

316
00:21:55,840 –> 00:21:58,960
until the first unmodeled interaction occurs.

317
00:21:58,960 –> 00:22:02,480
At that point there is no single locus of truth.

318
00:22:02,480 –> 00:22:07,440
Identity is smeared across code, configuration, and hidden assumptions.

319
00:22:07,440 –> 00:22:09,120
So the platform does not intervene.

320
00:22:09,120 –> 00:22:12,800
Fabrics engine will happily accept whatever id you handed

321
00:22:12,800 –> 00:22:15,280
in a big-int column you pretend is a surrogate.

322
00:22:15,280 –> 00:22:19,120
It will distribute inserts across nodes, commit files,

323
00:22:19,120 –> 00:22:22,240
and expose the table through SQL and Power BI.

324
00:22:22,240 –> 00:22:26,720
It has no intrinsic reason to distrust your application level sequence.

325
00:22:26,720 –> 00:22:30,720
It cannot distinguish your fake physics from actual constraints.

326
00:22:30,720 –> 00:22:32,000
That is the core failure.

327
00:22:32,000 –> 00:22:35,680
You try to replicate determinism in a layer that cannot enforce it.

328
00:22:35,680 –> 00:22:38,000
The application tier is mutable.

329
00:22:38,000 –> 00:22:41,280
It is versioned, redeployed, refactored, and replaced.

330
00:22:41,280 –> 00:22:46,400
Pipelines are edited, notebooks are copied, data flows are cloned.

331
00:22:46,400 –> 00:22:50,720
Every change to that logic is a change to how identity is assigned.

332
00:22:50,720 –> 00:22:53,600
The engine tier is not mutable in that way.

333
00:22:53,600 –> 00:22:57,200
Identity columns in fabric cannot be receded, they cannot be overridden,

334
00:22:57,200 –> 00:23:00,480
they cannot be manually populated with identity insert.

335
00:23:00,480 –> 00:23:03,600
The system deliberately withholds those escape hatches

336
00:23:03,600 –> 00:23:08,080
because every one of them is a path back to application level chaos.

337
00:23:08,080 –> 00:23:11,840
When you generate keys outside the engine, you are not being clever.

338
00:23:11,840 –> 00:23:15,200
You are assuming responsibility for concurrency distribution,

339
00:23:15,200 –> 00:23:18,480
ordering, and replayability across every execution context

340
00:23:18,480 –> 00:23:19,920
that touches that table.

341
00:23:19,920 –> 00:23:22,560
You will not carry that load consistently.

342
00:23:22,560 –> 00:23:25,840
Fabrics identity columns are the admission that this burden

343
00:23:25,840 –> 00:23:28,000
never belonged in your code.

344
00:23:28,000 –> 00:23:32,560
They relocate identity generation to the only actor that can observe all rights,

345
00:23:32,560 –> 00:23:35,440
coordinate all nodes, and refuse all violations.

346
00:23:35,440 –> 00:23:38,800
The moment you accept that, every clever workaround you wrote

347
00:23:38,800 –> 00:23:43,680
stops looking like engineering and starts looking like entropy disguised as logic.

348
00:23:43,680 –> 00:23:46,640
Incident 2, Lakehouse identity collapse.

349
00:23:46,640 –> 00:23:50,480
Now move from biased instruments to the store of record itself.

350
00:23:50,480 –> 00:23:56,400
The Lakehouse is sold to US convergence, one place, one copy, one truth.

351
00:23:56,400 –> 00:24:00,960
You centralize data from CRM, ERP, HR, Finance, Telemetry.

352
00:24:00,960 –> 00:24:04,320
You convince the organization that everything lives here now.

353
00:24:04,320 –> 00:24:06,240
You do not give the engine identity.

354
00:24:06,240 –> 00:24:10,240
You lend raw zones, bronze, silver, gold.

355
00:24:10,240 –> 00:24:13,520
You partition by date, by region, by business unit.

356
00:24:13,520 –> 00:24:15,120
You append, you absurd, you merge.

357
00:24:15,120 –> 00:24:17,520
You backfill last quarter, you reprocess last year.

358
00:24:17,520 –> 00:24:21,280
You migrate a legacy warehouse and stitch it into the same tables.

359
00:24:21,280 –> 00:24:24,880
Every one of those operations carries a belief about same customer,

360
00:24:24,880 –> 00:24:27,360
same employee, same asset.

361
00:24:27,360 –> 00:24:30,160
None of those beliefs are enforced as constraints.

362
00:24:30,160 –> 00:24:32,160
They are encoded as join conditions.

363
00:24:32,160 –> 00:24:35,280
You then hit the first real test, a structural change.

364
00:24:35,280 –> 00:24:38,560
The CRM system is replaced, customer IDs change format.

365
00:24:38,560 –> 00:24:43,200
Some are mapped, some are retired, HR merges to employee directories.

366
00:24:43,200 –> 00:24:46,160
Asset management re-keys equipment after an acquisition.

367
00:24:46,160 –> 00:24:49,920
Each upstream team promises we preserved mappings.

368
00:24:49,920 –> 00:24:53,520
They ship CSVs with old and new keys, maybe with effective dates.

369
00:24:53,520 –> 00:24:56,400
You write transformation logic to align histories.

370
00:24:56,400 –> 00:24:58,960
You treat these mapping tables as oracles.

371
00:24:58,960 –> 00:25:01,840
You believe they will remain correct under backfill.

372
00:25:01,840 –> 00:25:04,080
Then the inevitable happens.

373
00:25:04,080 –> 00:25:09,520
A late migration file arrives with slightly different mappings for a subset of customers.

374
00:25:09,520 –> 00:25:12,960
A vendor reruns an export with corrected joins.

375
00:25:12,960 –> 00:25:18,880
Someone notices a gap and replace 12 months of CRM into the same landing folder.

376
00:25:18,880 –> 00:25:20,960
Your lake house tables accept all of it.

377
00:25:20,960 –> 00:25:24,400
The same human now appears as multiple final keys,

378
00:25:24,400 –> 00:25:28,400
depending on which mapping was applied at which time in which pipeline.

379
00:25:28,400 –> 00:25:31,200
Old key to new key mapping A was used in one run.

380
00:25:31,200 –> 00:25:32,880
Mapping B was used in another.

381
00:25:32,880 –> 00:25:34,240
Both results are present.

382
00:25:34,240 –> 00:25:40,960
Both are considered valid because no surrogate in the warehouse asserts that these rows

383
00:25:40,960 –> 00:25:42,560
are mutually exclusive.

384
00:25:42,560 –> 00:25:45,280
From your perspective, identity has collapsed.

385
00:25:45,280 –> 00:25:47,520
From the engine’s perspective, nothing broke.

386
00:25:47,520 –> 00:25:51,440
It has two rows, each with distinct values, each passing type checks.

387
00:25:51,440 –> 00:25:53,360
The lake house did not lose identity.

388
00:25:53,360 –> 00:25:54,560
It never owned it.

389
00:25:54,560 –> 00:25:56,400
This is not a theoretical edge case.

390
00:25:56,400 –> 00:26:00,080
It is how large organizations actually evolve systems.

391
00:26:00,080 –> 00:26:02,080
They replace applications incrementally.

392
00:26:02,080 –> 00:26:03,280
They migrate in waves.

393
00:26:03,280 –> 00:26:06,000
They discover bad mappings and correct them.

394
00:26:06,000 –> 00:26:08,720
After data has already flowed downstream.

395
00:26:08,720 –> 00:26:14,400
Without engine-owned surrogates, every correction is an addition, not a substitution.

396
00:26:14,400 –> 00:26:16,240
You think you are fixing customers.

397
00:26:16,240 –> 00:26:17,360
You are forking them.

398
00:26:17,360 –> 00:26:22,720
Facts already loaded against the old representation remain bound to that phantom entity.

399
00:26:22,720 –> 00:26:25,280
New facts bind to the corrected one.

400
00:26:25,280 –> 00:26:28,480
Backfills bind to whichever path the code took that day.

401
00:26:28,480 –> 00:26:32,640
The entity graph becomes a probabilistic cloud around each real world object.

402
00:26:32,640 –> 00:26:34,320
No row is wrong in isolation.

403
00:26:34,320 –> 00:26:36,000
The constellation is wrong as a whole.

404
00:26:36,000 –> 00:26:37,920
Replay makes it worse.

405
00:26:37,920 –> 00:26:41,600
You decide to standardize all history under the new keys.

406
00:26:41,600 –> 00:26:42,960
You truncate silver.

407
00:26:42,960 –> 00:26:46,640
You replay bronze into silver with updated mapping logic.

408
00:26:46,640 –> 00:26:48,400
Some paths now collapse.

409
00:26:48,400 –> 00:26:50,000
Others split differently.

410
00:26:50,000 –> 00:26:54,560
Some drop entirely because the mapping files no longer contain obsolete keys.

411
00:26:54,560 –> 00:26:58,160
If identity is external, the warehouse produces a new universe.

412
00:26:58,160 –> 00:27:00,720
Facts reconnect to different dimension rows.

413
00:27:00,720 –> 00:27:04,960
Slowly changing dimension versions roll up under different anchors.

414
00:27:04,960 –> 00:27:07,840
Time series attached to customer X last week.

415
00:27:07,840 –> 00:27:11,840
Now attached to a different representation of customer X this week.

416
00:27:11,840 –> 00:27:13,360
You have not just changed state.

417
00:27:13,360 –> 00:27:16,080
You have changed which state was ever considered real.

418
00:27:16,080 –> 00:27:18,640
In this environment lineage diagrams lie to you.

419
00:27:18,640 –> 00:27:21,120
They show arrows from raw to silver to gold.

420
00:27:21,120 –> 00:27:23,200
They show tables feeding reports.

421
00:27:23,200 –> 00:27:27,760
They do not show that the referent of a given business key has shifted three times in a year

422
00:27:27,760 –> 00:27:29,280
with no structural trace.

423
00:27:29,280 –> 00:27:32,400
Engine level identity columns change that physics.

424
00:27:32,400 –> 00:27:37,520
When the warehouse owns a big insurgut for each customer, each employee, each asset.

425
00:27:37,520 –> 00:27:41,440
Migration mappings become translations to that anchor.

426
00:27:41,440 –> 00:27:43,440
Not creators of new anchors.

427
00:27:43,440 –> 00:27:48,160
A bad mapping attaches the wrong business key to an existing surrogate.

428
00:27:48,160 –> 00:27:52,000
Fixing it corrects attributes without minting new identities.

429
00:27:52,000 –> 00:27:54,800
Backfills replay events against fixed surrogates.

430
00:27:54,800 –> 00:28:00,240
New systems supply new natural keys that are resolved once deterministically

431
00:28:00,240 –> 00:28:02,480
into existing or new surrogates.

432
00:28:02,480 –> 00:28:05,280
The entity cloud collapses around stable coordinates.

433
00:28:05,280 –> 00:28:10,880
Now when you truncate and replay, you are not asking the platform to invent a fresh ontology.

434
00:28:10,880 –> 00:28:18,480
You are asking it to recompute attributes and relationships around the same identity graph.

435
00:28:18,480 –> 00:28:23,200
If removing identity columns would cause that graph to mutate under replay,

436
00:28:23,200 –> 00:28:24,880
your architecture was not stable.

437
00:28:24,880 –> 00:28:28,160
It was a snapshot of a negotiation between code paths.

438
00:28:28,160 –> 00:28:30,080
The lake house did not betray you.

439
00:28:30,080 –> 00:28:32,720
It revealed that you never gave it ownership of identity.

440
00:28:32,720 –> 00:28:36,160
The inevitability of replay and divergence.

441
00:28:36,160 –> 00:28:38,640
Replay is not an operational convenience.

442
00:28:38,640 –> 00:28:41,280
It is the only honest test of your architecture.

443
00:28:41,280 –> 00:28:46,000
If you cannot delete a data set, rerun the exact same inputs

444
00:28:46,000 –> 00:28:48,880
through the exact same transformations

445
00:28:48,880 –> 00:28:51,680
and reconstruct the same identity graph

446
00:28:51,680 –> 00:28:54,720
then your system never owned causality.

447
00:28:54,720 –> 00:28:57,280
It only produced a plausible history once

448
00:28:57,280 –> 00:29:00,240
in a deterministic platform replays boring.

449
00:29:00,240 –> 00:29:02,880
Same files, same code, same keys.

450
00:29:02,880 –> 00:29:06,400
Facts bind to the same dimensions.

451
00:29:06,400 –> 00:29:09,440
Slowly changing entities follow the same version paths.

452
00:29:09,440 –> 00:29:13,920
Lineage diagrams are not just decorative, they are verifiable.

453
00:29:13,920 –> 00:29:18,720
A surrogate key sequence is an irreversible record of how the engine experienced time.

454
00:29:18,720 –> 00:29:22,240
In your current lake house, replays theatre.

455
00:29:22,240 –> 00:29:25,440
You re-execute pipelines to prove recoverability.

456
00:29:25,440 –> 00:29:30,000
You validate row counts, you check aggregates, you declare success when total saline.

457
00:29:30,000 –> 00:29:32,480
You never compare identity because you cannot.

458
00:29:32,480 –> 00:29:35,360
There is no invariant anchor to compare against.

459
00:29:35,360 –> 00:29:38,880
The absence of identity columns makes divergence inevitable.

460
00:29:38,880 –> 00:29:42,000
Distributed engines are free to choose different join orders,

461
00:29:42,000 –> 00:29:44,960
different partitioning, different write patterns on every run.

462
00:29:44,960 –> 00:29:48,400
Without engine owned surrogates, those choices leak into identity.

463
00:29:48,400 –> 00:29:51,040
The same business entity can emerge from replay

464
00:29:51,040 –> 00:29:53,280
with different internal coordinates.

465
00:29:53,280 –> 00:29:59,280
The same customer 123 is now row 5, then row 17, then row 42.

466
00:29:59,280 –> 00:30:02,880
Each time linked to slightly different attribute histories.

467
00:30:02,880 –> 00:30:05,040
You call this non-deterministic behavior.

468
00:30:05,040 –> 00:30:06,160
It is not.

469
00:30:06,160 –> 00:30:10,800
The system is perfectly deterministic given its current plans, statistics and inputs.

470
00:30:10,800 –> 00:30:16,800
It is your notion of identity that drifts because it is not bound to anything the engine treats as physics.

471
00:30:16,800 –> 00:30:18,320
Time stamps do not rescue you.

472
00:30:18,320 –> 00:30:21,920
They shift under backfill, under later-riving data, under clock skew.

473
00:30:21,920 –> 00:30:23,440
Hashes do not rescue you.

474
00:30:23,440 –> 00:30:26,000
Change the hash definition and you rewrite the past.

475
00:30:26,000 –> 00:30:29,680
Application generated IDs do not rescue you.

476
00:30:29,680 –> 00:30:33,360
Concurrency and code evolution guarantee that over time,

477
00:30:33,360 –> 00:30:36,400
the same entity will be minted under multiple keys.

478
00:30:36,400 –> 00:30:40,240
Under these conditions, every replay is a forked universe.

479
00:30:40,240 –> 00:30:43,440
Your observability stack shows pipeline succeeded.

480
00:30:43,440 –> 00:30:46,800
Your BI layer shows numbers match with intolerance.

481
00:30:46,800 –> 00:30:49,600
Your AI workloads happily retrain on the new graph.

482
00:30:49,600 –> 00:30:54,240
None of them can tell you whether the identity space itself remains stable.

483
00:30:54,240 –> 00:30:57,280
This is where identity columns in fabric change the game.

484
00:30:57,280 –> 00:31:00,480
A big-int identity generated by the warehouse engine is not a label.

485
00:31:00,480 –> 00:31:03,440
It is a causal coordinate, each insert consumes one.

486
00:31:03,440 –> 00:31:08,960
That mapping from event to surrogate is part of the system’s execution,

487
00:31:08,960 –> 00:31:10,880
not your code’s suggestion.

488
00:31:10,880 –> 00:31:16,080
It is governed by the same distributed allocation algorithm on every run.

489
00:31:16,080 –> 00:31:18,800
When you replay with identity columns in place,

490
00:31:18,800 –> 00:31:22,080
you are not relying on row order or time stampuristics.

491
00:31:22,080 –> 00:31:26,080
You are testing whether the same inputs under the same transformation logic

492
00:31:26,080 –> 00:31:28,480
traverse the same causal path through the engine.

493
00:31:28,480 –> 00:31:30,720
If they do the same surrogate sequences appear.

494
00:31:30,720 –> 00:31:35,360
If they do not, you have proof of divergence at the only level that matters.

495
00:31:35,360 –> 00:31:37,920
This is the definition of owning your system.

496
00:31:37,920 –> 00:31:41,360
Identity is no longer a side effect of application behavior.

497
00:31:41,360 –> 00:31:45,840
It is an artifact of engine execution without that your lineage story is fiction.

498
00:31:45,840 –> 00:31:51,200
You cannot assert that fact F was always linked to dimension D through history.

499
00:31:51,200 –> 00:31:55,280
You can only assert that right now some join produces that pairing.

500
00:31:55,280 –> 00:31:59,840
If a future replay silently rebinds F to a different D,

501
00:31:59,840 –> 00:32:01,840
your audits become unprovable.

502
00:32:01,840 –> 00:32:05,200
Replay will happen. Migrations, corrections, model changes,

503
00:32:05,200 –> 00:32:10,000
regulation, disaster recovery, they all force you to run history again.

504
00:32:10,000 –> 00:32:15,360
With application level identity, each replay is a new negotiation with entropy.

505
00:32:15,360 –> 00:32:20,720
With engine level identity, each replay is a verification that causality is still intact.

506
00:32:20,720 –> 00:32:22,240
Divergence is not a risk.

507
00:32:22,240 –> 00:32:26,720
It is the default outcome when you refuse to give the system an invariant anchor.

508
00:32:26,720 –> 00:32:28,480
Identity columns are that anchor.

509
00:32:28,480 –> 00:32:32,640
They are the point where fabric stops letting replay, reinvent your universe,

510
00:32:32,640 –> 00:32:35,200
and starts treating it as a test you can fail.

511
00:32:35,200 –> 00:32:37,760
The architectural boundary transformation.

512
00:32:37,760 –> 00:32:39,600
You now know where entropy comes from.

513
00:32:39,600 –> 00:32:43,440
The only remaining question is where the system is allowed to stop trusting you.

514
00:32:43,440 –> 00:32:45,200
That boundary is not ingestion.

515
00:32:45,200 –> 00:32:48,480
Ingestion is the membrane between your chaos and fabric storage.

516
00:32:48,480 –> 00:32:51,920
Files arrive, streams land, tables are mirrored.

517
00:32:51,920 –> 00:32:54,320
At this layer ambiguity is not a bug.

518
00:32:54,320 –> 00:32:55,520
It is a requirement.

519
00:32:55,520 –> 00:32:59,520
If ingestion refused anything without pristine identity,

520
00:32:59,520 –> 00:33:02,960
most of your critical data would never enter the platform.

521
00:33:02,960 –> 00:33:08,400
The engine accepts conflicting keys overlapping histories and inconsistent schemas

522
00:33:08,400 –> 00:33:12,560
because its only job here is to persist what happened upstream.

523
00:33:12,560 –> 00:33:15,360
It writes down your contradictions with perfect fidelity.

524
00:33:15,360 –> 00:33:17,200
The boundary is not consumption.

525
00:33:17,200 –> 00:33:21,200
By the time a semantic model or a report or an AI workload

526
00:33:21,200 –> 00:33:26,400
touches the data, identity has already either been enforced or abandoned.

527
00:33:26,400 –> 00:33:28,880
Consumption layers can choose filters.

528
00:33:28,880 –> 00:33:31,440
They can choose which version of an entity to expose.

529
00:33:31,440 –> 00:33:34,720
They cannot retroactively mint causality.

530
00:33:34,720 –> 00:33:37,040
When you try to fix it in the model,

531
00:33:37,040 –> 00:33:40,320
you are painting numbers on a broken clock face.

532
00:33:40,320 –> 00:33:46,000
Fabrics only rational place to assert ownership is the transformation layer.

533
00:33:46,000 –> 00:33:49,760
Transformation is where raw inputs are minted into ordered truth.

534
00:33:49,760 –> 00:33:52,560
It is where bronze becomes silver, silver becomes gold.

535
00:33:52,560 –> 00:33:56,320
It is where you decide which rows are facts, which are dimensions,

536
00:33:56,320 –> 00:34:00,640
which attributes are slowly changing, which keys define grain.

537
00:34:00,640 –> 00:34:04,160
Every one of those decisions is a statement about causality.

538
00:34:04,160 –> 00:34:07,200
If the engine does not enforce identity here, it never will.

539
00:34:07,200 –> 00:34:11,360
This is why fabrics identity columns live in warehouse tables,

540
00:34:11,360 –> 00:34:16,800
not in file metadata, not in power BI models, not in co-pilot configuration.

541
00:34:16,800 –> 00:34:23,120
The warehouse is the transform boundary made concrete, structured, relational, constrained.

542
00:34:23,120 –> 00:34:25,440
It is the first place the system can say.

543
00:34:25,440 –> 00:34:32,160
From this point forward, this row has a non-negotiable identity that exists independently of any upstream token.

544
00:34:32,160 –> 00:34:36,880
Inside this boundary, surrogate keys must be generated not inferred.

545
00:34:36,880 –> 00:34:40,560
You do not reuse business keys as primary identifiers.

546
00:34:40,560 –> 00:34:42,880
You do not delegate sequence to pipelines.

547
00:34:42,880 –> 00:34:50,000
You let the engine assign a big-and-tee surrogate at the moment the row crosses from ingested representation to modeled entity.

548
00:34:50,000 –> 00:34:53,200
That is the tick where the escapement engages.

549
00:34:53,200 –> 00:34:59,760
Before it events are unanchored, after it, every downstream operation is defined in terms of those surrogates.

550
00:34:59,760 –> 00:35:04,480
Transform is also where referential integrity becomes enforceable again.

551
00:35:04,480 –> 00:35:09,680
In files, you cannot guarantee that a fact references an existing dimension row.

552
00:35:09,680 –> 00:35:12,640
In a warehouse with identity columns you can.

553
00:35:12,640 –> 00:35:15,680
Facts carry foreign keys to engine-owned surrogates.

554
00:35:15,680 –> 00:35:19,680
Joins are no longer best effort guesses on composite natural keys.

555
00:35:19,680 –> 00:35:23,600
They are deterministic resolutions against a constrained space.

556
00:35:23,600 –> 00:35:28,720
This is what fabric stops trusting upstream identity a transform.

557
00:35:28,720 –> 00:35:32,800
Actually means it continues to ingest whatever upstream systems emit.

558
00:35:32,800 –> 00:35:36,400
It continues to expose whatever tables you build to any consumption tool,

559
00:35:36,400 –> 00:35:39,920
but at the point where you ask the platform to treat something as a dimension,

560
00:35:39,920 –> 00:35:44,000
as a fact as a conformed entity fabric asserts its own physics.

561
00:35:44,000 –> 00:35:48,960
Surrogate key sequences become the irreversible log of that physics.

562
00:35:48,960 –> 00:35:52,000
Timestamps become supporting evidence, not identity.

563
00:35:52,000 –> 00:35:56,640
Replay events become proofs that the same transform produces the same surrogates.

564
00:35:56,640 –> 00:35:59,360
Fabric does not correct identity at ingestion.

565
00:35:59,360 –> 00:36:01,360
It asserts ownership at transformation.

566
00:36:01,360 –> 00:36:03,360
That is where ambiguity ends.

567
00:36:03,360 –> 00:36:06,880
Outside that boundary ambiguity is tolerated even required,

568
00:36:06,880 –> 00:36:09,280
inside it ambiguity is a design error.

569
00:36:09,280 –> 00:36:13,600
If you try to smuggle application level identity past this line,

570
00:36:13,600 –> 00:36:15,520
the system will still execute.

571
00:36:15,520 –> 00:36:22,080
But every property you claim lineage, auditability, AI governance will be fiction.

572
00:36:22,080 –> 00:36:25,520
The transform layer is not just another step in a medallion diagram.

573
00:36:25,520 –> 00:36:30,240
It is the jurisdictional border between human belief and machine determinism.

574
00:36:30,240 –> 00:36:33,200
You either let the warehouse own identity there,

575
00:36:33,200 –> 00:36:38,160
or you accept that your entire platform remains a probabilistic approximation

576
00:36:38,160 –> 00:36:39,760
dressed up as a data model.

577
00:36:39,760 –> 00:36:41,520
There is no third option.

578
00:36:41,520 –> 00:36:44,240
Identity columns as causal anchors.

579
00:36:44,240 –> 00:36:47,120
You have seen identity columns as a ticking mechanism.

580
00:36:47,120 –> 00:36:48,720
Now you will see them as anchors.

581
00:36:48,720 –> 00:36:50,240
An anchor is not a label.

582
00:36:50,240 –> 00:36:55,520
It is a fixed point in space time that every future calculation must respect.

583
00:36:55,520 –> 00:36:58,480
In a deterministic platform identity is that anchor.

584
00:36:58,480 –> 00:36:59,920
Everything else is commentary.

585
00:36:59,920 –> 00:37:03,120
When you define a big-int identity in fabric warehouse,

586
00:37:03,120 –> 00:37:05,840
you are not asking the engine for a handy counter.

587
00:37:05,840 –> 00:37:08,480
You are giving it the right to assign causal coordinates.

588
00:37:08,480 –> 00:37:12,320
Each value is a specific irreversible acknowledgement.

589
00:37:12,320 –> 00:37:14,800
This row exists in this table,

590
00:37:14,800 –> 00:37:18,320
and the system has bound a unique coordinate to it.

591
00:37:18,320 –> 00:37:21,120
From that moment on, every join, every foreign key,

592
00:37:21,120 –> 00:37:23,680
every lineage trace is no longer by agreement.

593
00:37:23,680 –> 00:37:25,040
It is by enforcement.

594
00:37:25,040 –> 00:37:26,240
You lose control.

595
00:37:26,240 –> 00:37:28,560
You cannot choose the starting point.

596
00:37:28,560 –> 00:37:32,160
Fabric does not support seeds or custom increments for identity.

597
00:37:32,160 –> 00:37:33,680
You cannot choose the pattern.

598
00:37:33,680 –> 00:37:37,520
Values are allocated across nodes in ranges, not in need sequences.

599
00:37:37,520 –> 00:37:39,200
You cannot inject your own numbers.

600
00:37:39,200 –> 00:37:41,280
Identity in cert is disabled.

601
00:37:41,280 –> 00:37:43,440
You cannot recede to rewrite history.

602
00:37:43,440 –> 00:37:45,200
That loss is intentional.

603
00:37:45,200 –> 00:37:50,000
Human discretion over identity is the source of drift.

604
00:37:50,000 –> 00:37:53,360
Every time someone fixes a key, compresses gaps,

605
00:37:53,360 –> 00:37:58,400
or reuses a range, they are asserting that causality is negotiable.

606
00:37:58,400 –> 00:38:01,200
Fabric’s implementation removes that surface area.

607
00:38:01,200 –> 00:38:06,240
The warehouse engine is the only actor allowed to decide which events consume which coordinates.

608
00:38:06,240 –> 00:38:07,440
The trade is simple.

609
00:38:07,440 –> 00:38:09,120
You surrender aesthetics.

610
00:38:09,120 –> 00:38:11,040
You gain determinism.

611
00:38:11,040 –> 00:38:15,200
Look at the dimension table built around an identity, surrogate.

612
00:38:15,200 –> 00:38:18,560
Business keys arrive dirty, duplicated, or remapped.

613
00:38:18,560 –> 00:38:21,760
The warehouse assigns surrogates in the order it accepts rows.

614
00:38:21,760 –> 00:38:24,960
Multiple natural keys can point at the same surrogate over time.

615
00:38:24,960 –> 00:38:27,520
The same natural key can point at different surrogates

616
00:38:27,520 –> 00:38:30,640
if the business genuinely splits an entity.

617
00:38:31,200 –> 00:38:35,200
But the mapping between surrogate and physical row is not up for debate.

618
00:38:35,200 –> 00:38:37,040
Facts reference that surrogate.

619
00:38:37,040 –> 00:38:39,440
AI features reference that surrogate.

620
00:38:39,440 –> 00:38:41,760
Lineage systems follow that surrogate.

621
00:38:41,760 –> 00:38:45,600
When a correction occurs, you change attributes or reassign business keys.

622
00:38:45,600 –> 00:38:47,120
You do not change the anchor.

623
00:38:47,120 –> 00:38:51,840
This is what stops alternative histories from silently coexisting.

624
00:38:51,840 –> 00:38:57,360
Without an anchor, your customer 123 can be redefined three times.

625
00:38:57,360 –> 00:39:01,840
And every time downstream joins will happily recompute reality.

626
00:39:01,840 –> 00:39:07,600
With an engine-owned surrogate, customer 123 is now just an attribute.

627
00:39:07,600 –> 00:39:12,880
The real identity is the big int the system emitted when it first accepted that row.

628
00:39:12,880 –> 00:39:18,080
Change the business key and you are updating a description not moving the anchor.

629
00:39:18,080 –> 00:39:20,240
That distinction is everything.

630
00:39:20,240 –> 00:39:24,560
It is why replay becomes a validation instead of a reinvention.

631
00:39:24,560 –> 00:39:31,040
It is why audits become about proving that surrogate X had these attributes at these times.

632
00:39:31,040 –> 00:39:35,680
Not about arguing whether customer 123 meant the same thing last year.

633
00:39:35,680 –> 00:39:40,480
It is why referential integrity in the warehouse is no longer a set of polite constraints,

634
00:39:40,480 –> 00:39:42,800
but a concrete graph the engine defends.

635
00:39:42,800 –> 00:39:44,880
The anchor also survives scale.

636
00:39:44,880 –> 00:39:49,840
Distributed identity allocation in fabric means values are not ordered globally,

637
00:39:49,840 –> 00:39:51,840
but they are unique by construction.

638
00:39:51,840 –> 00:39:57,360
Note A and Note B can ingest in parallel without coordination at the application tier.

639
00:39:57,360 –> 00:39:59,280
Ranges are pre-allocated.

640
00:39:59,280 –> 00:40:04,480
Once a value is consumed on any node, it is burned for that table forever.

641
00:40:04,480 –> 00:40:05,760
No retry, no reuse.

642
00:40:05,760 –> 00:40:06,960
You might see gaps.

643
00:40:06,960 –> 00:40:08,560
You might see jumps.

644
00:40:08,560 –> 00:40:11,680
That is the visible artifact of parallel causality.

645
00:40:11,680 –> 00:40:13,520
What you will not see is collision.

646
00:40:13,520 –> 00:40:18,720
In this model, your surrogate key sequences are not just implementation details.

647
00:40:18,720 –> 00:40:21,520
They are the visible edge of the underlying physics.

648
00:40:22,080 –> 00:40:27,360
A monotonically increasing, never-used series of big hints is how the engine

649
00:40:27,360 –> 00:40:30,560
exposes the fact that every row was anchored exactly once.

650
00:40:30,560 –> 00:40:33,280
If you strip identity columns away, you remove those anchors.

651
00:40:33,280 –> 00:40:38,160
You are back to a world where identity is an emergent property of business keys and timing,

652
00:40:38,160 –> 00:40:43,840
where replay is probabilistic, where AI is grounded in graphs that can be reconfigured by code changes.

653
00:40:43,840 –> 00:40:45,600
With them, you have a causal fabric.

654
00:40:45,600 –> 00:40:47,040
Facts cannot float free.

655
00:40:47,040 –> 00:40:49,600
Dimensions cannot be silently overwritten.

656
00:40:49,600 –> 00:40:54,400
Backfills cannot remap history without leaving scars in the surrogate space.

657
00:40:54,400 –> 00:40:58,480
The system still does what you tell it, but now, when you tell it to lie,

658
00:40:58,480 –> 00:41:00,560
it will lie in ways you can detect.

659
00:41:00,560 –> 00:41:01,760
That is what an anchor does.

660
00:41:01,760 –> 00:41:03,440
It does not make the ocean calm.

661
00:41:03,440 –> 00:41:05,840
It makes your position non-negotiable.

662
00:41:05,840 –> 00:41:09,360
Incident three, co-pilot and the hallucination of certainty.

663
00:41:09,360 –> 00:41:14,560
You build the clock, you wired the anchors, now you handed the whole mechanism to an interpreter

664
00:41:14,560 –> 00:41:15,760
and asked it to speak.

665
00:41:15,760 –> 00:41:17,840
You enabled co-pilot.

666
00:41:17,840 –> 00:41:20,720
From co-pilot’s perspective, your estate is not a mess.

667
00:41:20,720 –> 00:41:21,680
It is a graph.

668
00:41:21,680 –> 00:41:26,800
Tables, relationships, measures, documents, logs, it traverses that graph exactly as exposed.

669
00:41:26,800 –> 00:41:29,600
It does not infer ethics, it does not infer architecture.

670
00:41:29,600 –> 00:41:31,920
It treats everything it can see as intentional.

671
00:41:31,920 –> 00:41:35,040
You ask a question that every executive eventually asks.

672
00:41:35,040 –> 00:41:37,200
Show me everything we know about this customer.

673
00:41:37,200 –> 00:41:40,320
Co-pilot fans out, it hits the warehouse, it hits the lake house,

674
00:41:40,320 –> 00:41:45,840
it hits semantic models and share point files and teams chats summarizing incidents.

675
00:41:45,840 –> 00:41:48,960
It sees three customer rows that match the same natural key.

676
00:41:48,960 –> 00:41:54,000
It sees facts bound to each, it sees tickets, invoices, churn risk scores

677
00:41:54,000 –> 00:41:56,320
and meeting notes referencing all of them.

678
00:41:56,320 –> 00:41:58,720
You experience that as one human, the graph does not.

679
00:41:58,720 –> 00:42:03,200
The graph presents three nodes with partially overlapping evidence.

680
00:42:03,200 –> 00:42:07,840
Co-pilot does exactly what a probabilistic model is trained to do, interpolate.

681
00:42:07,840 –> 00:42:11,840
It merges attributes, picks stronger signals, fills gaps.

682
00:42:11,840 –> 00:42:13,040
It writes you a narrative.

683
00:42:13,040 –> 00:42:17,360
It tells you this customer’s lifetime value, recent complaints,

684
00:42:17,360 –> 00:42:20,720
regions of operation and open risks.

685
00:42:20,720 –> 00:42:23,520
It synthesizes across the duplicates you allowed,

686
00:42:23,520 –> 00:42:25,440
smoothing contradictions into prose.

687
00:42:25,440 –> 00:42:28,640
From your chair, this looks like hallucination.

688
00:42:28,640 –> 00:42:30,800
From co-pilot’s chair, this is obedience.

689
00:42:30,800 –> 00:42:32,800
Co-pilot did not hallucinate reality.

690
00:42:32,800 –> 00:42:34,800
It interpolated your ambiguity.

691
00:42:34,800 –> 00:42:36,800
You try to fix it at the prompt layer.

692
00:42:36,800 –> 00:42:38,160
You constrain scope.

693
00:42:38,160 –> 00:42:40,160
You say only use this data set.

694
00:42:40,480 –> 00:42:44,400
You add grounding rules. You specify that customer business key is unique.

695
00:42:44,400 –> 00:42:50,720
None of that changes the underlying fact that in storage, that column is not unique and never was.

696
00:42:50,720 –> 00:42:53,840
Retrieval augmented generation makes this worse, not better.

697
00:42:53,840 –> 00:42:57,520
You build a vector index over documents that reference customers.

698
00:42:57,520 –> 00:43:00,320
You embed emails, contracts, call transcripts.

699
00:43:00,320 –> 00:43:04,560
You attach metadata linking each chunk to a customer key from the warehouse.

700
00:43:04,560 –> 00:43:06,160
That key is already ambiguous.

701
00:43:06,160 –> 00:43:09,440
Your index now encodes that ambiguity into dense vectors.

702
00:43:09,440 –> 00:43:14,000
At query time, rag he pulls multiple chunks for customer 123.

703
00:43:14,000 –> 00:43:19,040
Some belong to the original entity, some to the forked clone created during a migration,

704
00:43:19,040 –> 00:43:22,720
some to a temporary placeholder ID that was never cleaned up.

705
00:43:22,720 –> 00:43:25,440
Similar text reinforces the retrieval,

706
00:43:25,440 –> 00:43:28,880
because vector search reads it as “corroboration.”

707
00:43:28,880 –> 00:43:32,720
Co-pilot sees multiple pieces of evidence that all seem to agree.

708
00:43:32,720 –> 00:43:34,080
It raises its confidence.

709
00:43:34,080 –> 00:43:37,120
The answer becomes more fluent, more detailed, more wrong.

710
00:43:37,120 –> 00:43:39,280
You are not watching spontaneous fiction.

711
00:43:39,280 –> 00:43:44,080
You are watching a stochastic parrot amplifying the structural indecision of your identity graph.

712
00:43:44,080 –> 00:43:48,080
The more richly you describe your entities in unstructured form,

713
00:43:48,080 –> 00:43:51,520
the more surface area you give the model to entangle them.

714
00:43:51,520 –> 00:43:54,000
Deterministic identities, the only break,

715
00:43:54,000 –> 00:43:57,440
when the warehouse owns surrogates and everything that matters,

716
00:43:57,440 –> 00:44:01,600
facts, documents, features, binds to those surrogates.

717
00:44:01,600 –> 00:44:05,920
Co-pilot’s retrieval, layer, has a stable join key.

718
00:44:05,920 –> 00:44:10,800
Vector stores can index chunks against engine-owned IDs instead of business tokens.

719
00:44:10,800 –> 00:44:15,920
Ragn can retrieve all and only the evidence attached to that surrogate.

720
00:44:15,920 –> 00:44:19,680
If that surrogate is wrong, the error is singular and correctable.

721
00:44:19,680 –> 00:44:20,960
Fix the mapping once.

722
00:44:20,960 –> 00:44:24,240
Every downstream answer shifts in a traceable way.

723
00:44:24,240 –> 00:44:30,560
Without that surrogate, fixing one manifestation of ambiguity leaves countless others untouched.

724
00:44:30,560 –> 00:44:35,600
The model continues to interpolate across a graph that never snapped to a single truth.

725
00:44:35,600 –> 00:44:37,520
You will not deprobabilize AI.

726
00:44:37,520 –> 00:44:38,400
That is not the point.

727
00:44:38,400 –> 00:44:43,120
What you can do is remove unnecessary randomness from what it stands on.

728
00:44:43,120 –> 00:44:46,160
Identity columns do not make co-pilot deterministic.

729
00:44:46,160 –> 00:44:48,880
They make the substrate less incoherent.

730
00:44:48,880 –> 00:44:51,440
They ensure that when the model invents,

731
00:44:51,440 –> 00:44:57,600
it is inventing at the edge of knowledge not in the void created by your refusal to enforce who is who.

732
00:44:57,600 –> 00:44:59,600
You wanted co-pilot to reveal insight.

733
00:44:59,600 –> 00:45:01,520
It revealed architecture.

734
00:45:01,520 –> 00:45:04,960
It showed you that, without engine-level identity,

735
00:45:04,960 –> 00:45:12,880
every confident sentence about a customer and employee or an asset is built on top of a graph that never decided which node was real.

736
00:45:12,880 –> 00:45:14,720
AI did not create that problem.

737
00:45:14,720 –> 00:45:18,320
It just executed faster on the ambiguity you allowed to exist.

738
00:45:18,320 –> 00:45:21,680
Systemic trust versus human belief.

739
00:45:21,680 –> 00:45:25,200
Up to now you have treated identity as a matter of belief.

740
00:45:25,200 –> 00:45:28,720
You believe a column is unique because the specification says so.

741
00:45:28,720 –> 00:45:32,080
You believe a pipeline is safe because it has always worked in.

742
00:45:32,080 –> 00:45:35,920
You believe a model is trustworthy because it agrees with a prior report.

743
00:45:35,920 –> 00:45:37,280
None of that is systemic trust.

744
00:45:37,280 –> 00:45:39,520
It is habit, wrapped in narrative.

745
00:45:39,520 –> 00:45:41,040
Systemic trust is different.

746
00:45:41,040 –> 00:45:42,720
It is not about how you feel.

747
00:45:42,720 –> 00:45:44,880
It is about what the engine enforces.

748
00:45:44,880 –> 00:45:47,600
So when fabric generates a big int identity,

749
00:45:47,600 –> 00:45:49,760
it is not asking for your agreement.

750
00:45:49,760 –> 00:45:52,720
It is asserting a constraint you cannot bypass.

751
00:45:52,720 –> 00:45:54,320
That is systemic trust.

752
00:45:54,320 –> 00:45:59,120
You can rely on a property precisely because no human can casually violate it.

753
00:45:59,120 –> 00:46:00,880
Your belief sit on the other side.

754
00:46:00,880 –> 00:46:02,880
You believe guides solve uniqueness.

755
00:46:02,880 –> 00:46:03,680
They do not.

756
00:46:03,680 –> 00:46:07,040
They solve collision probability at generation time.

757
00:46:07,040 –> 00:46:12,080
They do nothing for referential integrity, replay determinism or entity collapse.

758
00:46:12,080 –> 00:46:14,320
You believe hashes are good enough.

759
00:46:14,320 –> 00:46:15,440
They are not.

760
00:46:15,440 –> 00:46:20,080
Change the hash definition and every prior key becomes obsolete.

761
00:46:20,080 –> 00:46:22,160
You believe governance documents matter.

762
00:46:22,160 –> 00:46:23,520
They do not at runtime.

763
00:46:23,520 –> 00:46:26,160
The system does not read your confluence pages.

764
00:46:26,160 –> 00:46:28,480
It executes your DDL.

765
00:46:28,480 –> 00:46:32,400
This is the psychological pivot identity columns force.

766
00:46:32,400 –> 00:46:35,200
You are no longer the final arbiter of identity.

767
00:46:35,200 –> 00:46:40,640
The engine is your role shifts from assigned keys to declare where enforcement is required.

768
00:46:40,640 –> 00:46:44,320
Once you create an identity column on a warehouse table,

769
00:46:44,320 –> 00:46:46,880
you have seeded control over sequence,

770
00:46:46,880 –> 00:46:50,000
over receding, over manual inserts.

771
00:46:50,000 –> 00:46:53,840
You have accepted that determinism is more important than discretion.

772
00:46:53,840 –> 00:46:56,400
Human intuition is a source of entropy.

773
00:46:56,400 –> 00:47:00,400
You are biased toward convenience, readability and short term fixes.

774
00:47:00,400 –> 00:47:02,400
You are biased toward exceptions.

775
00:47:02,400 –> 00:47:05,600
Just this once we will backfill directly into the key.

776
00:47:05,600 –> 00:47:08,080
Just this once we will reuse this range.

777
00:47:08,080 –> 00:47:10,880
Just this once we will correct IDs in place.

778
00:47:10,880 –> 00:47:13,360
Systems do not operate in just this once mode.

779
00:47:13,360 –> 00:47:15,120
They operate in always mode.

780
00:47:15,120 –> 00:47:20,640
Every time you smuggle identity decisions into an ad hoc script or an emergency notebook,

781
00:47:20,640 –> 00:47:22,160
you create a precedent.

782
00:47:22,160 –> 00:47:24,480
The platform will happily scale.

783
00:47:24,480 –> 00:47:27,840
Identity columns are designed to remove those escape routes.

784
00:47:27,840 –> 00:47:29,440
No identity insert.

785
00:47:29,440 –> 00:47:30,400
No recede.

786
00:47:30,400 –> 00:47:33,200
No control over allocation strategy.

787
00:47:33,200 –> 00:47:38,480
The engine does not trust your exceptions because exceptions are how entropy wins.

788
00:47:38,480 –> 00:47:40,720
You might experience this as hostility.

789
00:47:40,720 –> 00:47:44,000
You are blocked from repairing data by hand.

790
00:47:44,000 –> 00:47:47,920
You cannot compress gaps to satisfy auditors who want clean sequences.

791
00:47:47,920 –> 00:47:53,920
You cannot align warehouse IDs with legacy keys to make cross-system debugging easier.

792
00:47:53,920 –> 00:47:57,040
Every attempt to bend the physics runs into a wall.

793
00:47:57,040 –> 00:47:57,920
That is the point.

794
00:47:57,920 –> 00:48:02,720
Systemic trust is built on the absence of special cases.

795
00:48:02,720 –> 00:48:07,760
Once the warehouse owns identity, every right is subject to the same rules.

796
00:48:07,760 –> 00:48:12,400
Pipelines, notebooks, one-off scripts, they all pass through the same enforcement.

797
00:48:12,400 –> 00:48:14,000
You lose flexibility.

798
00:48:14,000 –> 00:48:15,120
You gain invariance.

799
00:48:15,120 –> 00:48:18,880
This is why best practices are irrelevant here.

800
00:48:18,880 –> 00:48:22,000
A best practice is a recommendation that can be ignored.

801
00:48:22,000 –> 00:48:25,520
An identity constraint is a law the engine will not relax.

802
00:48:25,520 –> 00:48:27,760
Governance documents are paper shields.

803
00:48:27,760 –> 00:48:32,640
They decay under staff turnover, vendo change, and operational pressure.

804
00:48:32,640 –> 00:48:35,920
Engine enforced identity does not care who is on call.

805
00:48:35,920 –> 00:48:38,480
It does not care which consultant wrote the last pipeline.

806
00:48:38,480 –> 00:48:39,760
Fabric is neutral in this.

807
00:48:39,760 –> 00:48:42,320
It does not praise you for using identity columns.

808
00:48:42,320 –> 00:48:44,240
It does not warn you if you choose not to.

809
00:48:44,240 –> 00:48:50,720
It simply exposes the consequences of both choices faster than your prior platforms.

810
00:48:50,720 –> 00:48:53,680
When you rely on human belief, divergence appears sooner.

811
00:48:53,680 –> 00:49:00,080
When you rely on systemic trust, divergence is pushed to the edges where architecture is genuinely ambiguous.

812
00:49:00,080 –> 00:49:03,440
Your job at this point is not to negotiate with the system.

813
00:49:03,440 –> 00:49:10,080
Your job is to decide whether you accept a world where identity is enforced by physics or a world

814
00:49:10,080 –> 00:49:12,720
where it is negotiated in code reviews.

815
00:49:12,720 –> 00:49:19,200
One gives you deterministic replay, auditable lineage, and bounded AI ambiguity.

816
00:49:19,200 –> 00:49:23,120
The other gives you stories you tell yourself about how things should work.

817
00:49:23,120 –> 00:49:25,680
The system does not listen to stories.

818
00:49:25,680 –> 00:49:27,200
It executes constraints.

819
00:49:27,200 –> 00:49:28,960
The end of best practices.

820
00:49:28,960 –> 00:49:31,040
You were trained to believe in best practices.

821
00:49:31,040 –> 00:49:32,320
You wrote them into wikis.

822
00:49:32,320 –> 00:49:33,440
You put them on slides.

823
00:49:33,440 –> 00:49:35,280
You embedded them in code reviews.

824
00:49:35,280 –> 00:49:37,200
Always use composite keys here.

825
00:49:37,200 –> 00:49:39,360
Never trust this upstream field.

826
00:49:39,360 –> 00:49:41,840
Remember to deduplicate before loading gold.

827
00:49:41,840 –> 00:49:44,960
Entropy treated those sentences as background noise.

828
00:49:44,960 –> 00:49:47,040
A best practice is an optional behavior.

829
00:49:47,040 –> 00:49:48,560
It is a social contract.

830
00:49:48,560 –> 00:49:52,480
It assumes continuity of memory, continuity of staff, continuity of context.

831
00:49:52,480 –> 00:49:54,000
None of that exists at scale.

832
00:49:54,000 –> 00:49:55,040
Teams change.

833
00:49:55,040 –> 00:49:56,240
Vendors rotate.

834
00:49:56,240 –> 00:49:57,600
Requirements shift.

835
00:49:57,600 –> 00:49:59,040
Deadlines compress.

836
00:49:59,040 –> 00:49:59,920
Under pressure.

837
00:49:59,920 –> 00:50:02,480
Best practices are the first thing to go.

838
00:50:02,480 –> 00:50:05,120
Identity does not survive on suggestions.

839
00:50:05,120 –> 00:50:09,920
If a rule can be broken by a tired engineer at 2am, it is not protection.

840
00:50:09,920 –> 00:50:11,520
It is decoration.

841
00:50:11,520 –> 00:50:16,800
Your entire identity strategy has been built on that kind of decoration.

842
00:50:16,800 –> 00:50:19,200
Guidelines about natural keys.

843
00:50:19,200 –> 00:50:21,600
Conventions about hash definitions.

844
00:50:21,600 –> 00:50:25,360
Shared understanding of which columns really mean the same thing.

845
00:50:25,360 –> 00:50:27,040
The system never read any of it.

846
00:50:27,040 –> 00:50:28,960
Fabric is not hostile to your best practices.

847
00:50:28,960 –> 00:50:30,320
It is indifferent.

848
00:50:30,320 –> 00:50:34,320
It executes only what is encoded as constraints and DDL.

849
00:50:34,320 –> 00:50:36,240
Every other instruction is commentary.

850
00:50:36,240 –> 00:50:39,760
When you tell a team, we prefer GUIDs for identity.

851
00:50:39,760 –> 00:50:41,920
Fabric hears nothing.

852
00:50:41,920 –> 00:50:45,520
When you tell them, never backfill directly into this table.

853
00:50:45,520 –> 00:50:46,960
Fabric hears nothing.

854
00:50:46,960 –> 00:50:51,200
When you tell them, this column is unique by business definition.

855
00:50:51,200 –> 00:50:52,640
Fabric hears nothing.

856
00:50:52,640 –> 00:50:56,000
This is why identity columns are not a recommendation pattern.

857
00:50:56,000 –> 00:50:57,120
They are required physics.

858
00:50:57,120 –> 00:50:58,720
You are not encouraged to use them.

859
00:50:58,720 –> 00:51:00,000
You are constrained by them.

860
00:51:00,000 –> 00:51:02,560
The moment you declare a big-int identity,

861
00:51:02,560 –> 00:51:05,920
you convert identity from culture to law.

862
00:51:05,920 –> 00:51:07,440
No future optimization.

863
00:51:07,440 –> 00:51:08,720
No emergency fix.

864
00:51:08,720 –> 00:51:11,840
No consultant shortcut can bypass that column.

865
00:51:11,840 –> 00:51:13,600
The engine will allocate values.

866
00:51:13,600 –> 00:51:15,360
The engine will refuse overrides.

867
00:51:15,360 –> 00:51:16,800
The engine will retain gaps.

868
00:51:16,800 –> 00:51:19,360
In that world, best practice loses meaning.

869
00:51:19,360 –> 00:51:22,560
You do not have a best practice for using gravity.

870
00:51:22,560 –> 00:51:24,960
You have a description of how it behaves.

871
00:51:24,960 –> 00:51:28,400
Identity columns move identity into that category.

872
00:51:28,400 –> 00:51:30,320
They are not subject to design debates.

873
00:51:30,320 –> 00:51:33,200
They are a property of the platform you either align with

874
00:51:33,200 –> 00:51:35,600
or fight against at your own cost.

875
00:51:35,600 –> 00:51:37,520
Look at your existing governance.

876
00:51:37,520 –> 00:51:41,200
Pages of standards about naming, about SCD types,

877
00:51:41,200 –> 00:51:43,200
about surrogate key semantics.

878
00:51:43,200 –> 00:51:47,280
All of them premised on the idea that humans will remember and comply.

879
00:51:47,280 –> 00:51:51,120
Now map those documents against the incidents you have already seen.

880
00:51:51,120 –> 00:51:54,400
Duplicate customers, forked entities, AI interpolation.

881
00:51:54,400 –> 00:51:58,880
Every failure is a place where someone treated a best practice as optional.

882
00:51:58,880 –> 00:52:01,040
The lesson is not that you need more training.

883
00:52:01,040 –> 00:52:04,960
The lesson is that identity cannot be left in the space of advice.

884
00:52:04,960 –> 00:52:06,320
Fabrics move is clear.

885
00:52:06,320 –> 00:52:08,400
It is shifting from recommending patterns

886
00:52:08,400 –> 00:52:11,600
to making certain classes of failure materially impossible.

887
00:52:11,600 –> 00:52:14,000
You cannot accidentally recede an identity.

888
00:52:14,000 –> 00:52:16,160
You cannot casually insert your own values.

889
00:52:16,160 –> 00:52:19,520
You cannot tune allocation to satisfy aesthetic preferences.

890
00:52:19,520 –> 00:52:21,600
Those guardrails are not UX choices.

891
00:52:21,600 –> 00:52:23,040
They are entropy controls.

892
00:52:23,040 –> 00:52:24,720
This is the end of we prefer.

893
00:52:24,720 –> 00:52:27,120
In the old world you preferred surrogate keys.

894
00:52:27,120 –> 00:52:29,840
In the old world you preferred deterministic joins.

895
00:52:29,840 –> 00:52:33,200
In the old world you preferred replayable pipelines.

896
00:52:33,200 –> 00:52:36,400
In practice you accepted exceptions whenever they were convenient.

897
00:52:36,400 –> 00:52:41,200
The accumulation of those exceptions is what you now call technical debt.

898
00:52:41,200 –> 00:52:45,440
In the new world you either encode a property as a constraint

899
00:52:45,440 –> 00:52:48,080
or you admit it is negotiable.

900
00:52:48,080 –> 00:52:53,760
If uniqueness matters it lives in an identity-backed key with a supporting index.

901
00:52:53,760 –> 00:52:58,240
If referential integrity matters it lives in foreign keys to that identity.

902
00:52:58,240 –> 00:53:03,200
If replay determinism matters it lives in the expectation that identity columns

903
00:53:03,200 –> 00:53:06,160
will regenerate the same graph under the same transformations.

904
00:53:06,160 –> 00:53:07,920
Everything else is commentary.

905
00:53:07,920 –> 00:53:09,840
Best practices do not disappear.

906
00:53:09,840 –> 00:53:10,800
They relocate.

907
00:53:10,800 –> 00:53:13,520
They become about modeling choices above a layer

908
00:53:13,520 –> 00:53:15,200
whose physics you no longer control.

909
00:53:15,200 –> 00:53:16,320
You can debate grain.

910
00:53:16,320 –> 00:53:17,920
You can debate type handling.

911
00:53:17,920 –> 00:53:19,600
You can debate SCD strategies.

912
00:53:19,600 –> 00:53:22,560
You do not debate who owns identity.

913
00:53:22,560 –> 00:53:23,680
The engine does.

914
00:53:23,680 –> 00:53:26,720
This is uncomfortable.

915
00:53:26,720 –> 00:53:30,640
It removes the illusion that craftsmanship alone can keep a platform safe.

916
00:53:30,640 –> 00:53:34,000
It exposes the fact that many of your proudest patterns were fragile

917
00:53:34,000 –> 00:53:36,160
because they relied on humans never slipping.

918
00:53:36,160 –> 00:53:39,200
It replaces pride and cleverness with respect for constraint.

919
00:53:39,200 –> 00:53:40,160
That is the point.

920
00:53:40,160 –> 00:53:42,560
You were never going to out-remember entropy.

921
00:53:42,560 –> 00:53:44,320
You were never going to out-documented.

922
00:53:44,320 –> 00:53:46,400
You were never going to out-govern it.

923
00:53:46,400 –> 00:53:48,800
The only sustainable defense was always the same.

924
00:53:48,800 –> 00:53:52,480
Move identity out of the zone of preference and into the zone of enforcement.

925
00:53:52,480 –> 00:53:54,560
Fabric has now given you that mechanism.

926
00:53:54,560 –> 00:53:57,280
Whether you use it is no longer a matter of best practice.

927
00:53:57,280 –> 00:54:00,880
It is a matter of whether your architecture deserves to be trusted at all.

928
00:54:00,880 –> 00:54:02,400
Determinism at scale.

929
00:54:02,400 –> 00:54:07,600
So far everything I described holds on a single table, a single pipeline, a single replay.

930
00:54:07,600 –> 00:54:10,960
Now extended to the only scale that matters your estate.

931
00:54:10,960 –> 00:54:13,600
At small scale you can mistake luck for architecture.

932
00:54:13,600 –> 00:54:14,640
A handful of tables.

933
00:54:14,640 –> 00:54:15,760
One or two pipelines.

934
00:54:15,760 –> 00:54:16,800
Limited concurrency.

935
00:54:16,800 –> 00:54:18,400
Human memory covers gaps.

936
00:54:18,400 –> 00:54:21,280
Tribal knowledge patches missing constraints.

937
00:54:21,280 –> 00:54:24,400
When something diverges you fix it in place and move on.

938
00:54:24,400 –> 00:54:26,880
At scale those tricks stop working.

939
00:54:26,880 –> 00:54:29,280
A serious fabric deployment is not ten tables.

940
00:54:29,280 –> 00:54:30,480
It is thousands.

941
00:54:30,480 –> 00:54:31,840
Multiple warehouses.

942
00:54:31,840 –> 00:54:33,280
Multiple lake houses.

943
00:54:33,280 –> 00:54:34,480
Mirage sources.

944
00:54:34,480 –> 00:54:38,640
Dozens of teams shipping transformations independently.

945
00:54:38,640 –> 00:54:43,440
Hundreds of pipelines executing in parallel across time zones.

946
00:54:43,440 –> 00:54:45,120
Entropy multiplies.

947
00:54:45,120 –> 00:54:49,920
With every new boundary every source system has its own opinion about identity.

948
00:54:49,920 –> 00:54:52,080
Every domain has its own partial key.

949
00:54:52,080 –> 00:54:55,360
Every integration introduces another mapping.

950
00:54:55,360 –> 00:54:59,440
Without engine level enforcement each of those opinions is free to drift.

951
00:54:59,440 –> 00:55:01,440
You do not get one identity problem.

952
00:55:01,440 –> 00:55:03,920
You get a combinatorial explosion of them.

953
00:55:03,920 –> 00:55:06,320
Determinism is no longer an aesthetic preference.

954
00:55:06,320 –> 00:55:09,200
It is the only viable survival strategy.

955
00:55:09,200 –> 00:55:12,880
Identity columns are what make determinism composable at that scale.

956
00:55:12,880 –> 00:55:16,320
When each warehouse table owns an identity backed surrogate.

957
00:55:16,320 –> 00:55:20,480
The cost of joining two domains is not hope their natural keys align.

958
00:55:20,480 –> 00:55:23,440
It is defined how their surrogates relate.

959
00:55:23,440 –> 00:55:25,600
That is a finite local decision.

960
00:55:25,600 –> 00:55:26,960
Customer to policy.

961
00:55:26,960 –> 00:55:28,240
Employee to device.

962
00:55:28,240 –> 00:55:29,600
Acid to location.

963
00:55:29,600 –> 00:55:32,960
Each link is a foreign key between engine-owned anchors.

964
00:55:32,960 –> 00:55:35,840
Not a heuristic over ambiguous tokens.

965
00:55:35,840 –> 00:55:37,600
Lineage becomes tractable.

966
00:55:37,600 –> 00:55:41,360
At small scale you can trace an issue by eyeballing rows.

967
00:55:41,360 –> 00:55:44,080
At large scale you have no such luxury.

968
00:55:44,080 –> 00:55:48,720
You need automated systems that can say this report cell depends on this gold table row

969
00:55:48,720 –> 00:55:54,560
which depends on this silver row which originated from this raw file which came from this upstream feed.

970
00:55:54,560 –> 00:55:57,040
Without stable surrogates that path is fuzzy.

971
00:55:57,040 –> 00:55:59,840
With them it is a chain of key references.

972
00:55:59,840 –> 00:56:02,720
Replay events become regression tests.

973
00:56:02,720 –> 00:56:07,840
When you touch a critical transformation in a mature platform you cannot rely on intuition.

974
00:56:07,840 –> 00:56:11,440
You must know whether the change preserved identity or mutated it.

975
00:56:11,440 –> 00:56:14,320
A deterministic estate lets you do that.

976
00:56:14,320 –> 00:56:16,960
You replay a slice of history in a shadow environment.

977
00:56:16,960 –> 00:56:18,560
You compare surrogate graphs.

978
00:56:18,560 –> 00:56:21,920
If keys and relationships line up the change is safe.

979
00:56:21,920 –> 00:56:24,880
If they diverge you have a controlled failure.

980
00:56:24,880 –> 00:56:27,440
This is impossible if identity is emergent.

981
00:56:27,440 –> 00:56:31,840
At scale emergent identity produces phantom deltas on every run.

982
00:56:31,840 –> 00:56:34,320
Keys flip, relationships drift.

983
00:56:34,320 –> 00:56:38,160
Your diff tools show massive change where none exists.

984
00:56:38,160 –> 00:56:41,200
And you lose the signal of real divergence in the noise.

985
00:56:41,200 –> 00:56:43,200
You stop trusting your own validation.

986
00:56:43,200 –> 00:56:44,800
You start shipping blindly.

987
00:56:44,800 –> 00:56:48,320
Deterministic identity also constrains blast radius.

988
00:56:48,320 –> 00:56:53,440
When every table has an engine owned surrogate a bad transformation can corrupt attributes

989
00:56:53,440 –> 00:56:56,240
but it cannot silently respawn entities.

990
00:56:56,240 –> 00:56:57,600
The anchor remains.

991
00:56:57,600 –> 00:57:01,680
Downstream systems may see wrong data but they see it attached to the same keys.

992
00:57:01,760 –> 00:57:05,440
You can roll forward or back while preserving referential structure.

993
00:57:05,440 –> 00:57:09,600
Without that every incident risks structural collapse.

994
00:57:09,600 –> 00:57:13,120
A misconfigured backfill recomputes hashes differently.

995
00:57:13,120 –> 00:57:15,040
Suddenly foreign keys no longer match.

996
00:57:15,040 –> 00:57:16,720
Joins return empties.

997
00:57:16,720 –> 00:57:19,280
AI features break silently.

998
00:57:19,280 –> 00:57:21,440
Fixing it is not a correction.

999
00:57:21,440 –> 00:57:22,800
It is a resurrection effort.

1000
00:57:22,800 –> 00:57:28,880
Finally, determinism is what allows you to centralize without surrendering control.

1001
00:57:29,440 –> 00:57:33,200
Fabrics promise is one lake, one platform, many domains.

1002
00:57:33,200 –> 00:57:38,880
That is only coherent if every domain can rely on the platform to enforce the invariance they declare.

1003
00:57:38,880 –> 00:57:41,280
Identity columns are the primary invariant.

1004
00:57:41,280 –> 00:57:46,000
Once a team commits to engine owned surrogates they can publish artifacts

1005
00:57:46,000 –> 00:57:53,200
knowing that no other team’s pipeline will accidentally remap their entities by fixing a shared business key.

1006
00:57:53,200 –> 00:57:56,560
This is systemic trust projected across organizational boundaries.

1007
00:57:56,560 –> 00:58:01,040
If you try to run a global analytics estate on probabilistic identity

1008
00:58:01,040 –> 00:58:03,440
you are building a distributed guessing machine.

1009
00:58:03,440 –> 00:58:05,600
It will work until the day it matters most.

1010
00:58:05,600 –> 00:58:10,240
At that point every ambiguity you tolerate it will surface together

1011
00:58:10,240 –> 00:58:14,400
and you will not have the tools to distinguish noise from failure.

1012
00:58:14,400 –> 00:58:17,440
Deterministic identity at scale is not optional.

1013
00:58:17,440 –> 00:58:20,720
It is the minimum requirement for claiming you have a platform at all.

1014
00:58:20,720 –> 00:58:24,080
The post-human data platform.

1015
00:58:24,080 –> 00:58:28,240
You have been treating the platform as an assistant to your judgment.

1016
00:58:28,240 –> 00:58:30,480
A place to store what you already believe.

1017
00:58:30,480 –> 00:58:33,360
A place to calculate what you already decided matters.

1018
00:58:33,360 –> 00:58:35,840
Identity columns invert that relationship.

1019
00:58:35,840 –> 00:58:39,760
They are the first visible sign of a different kind of system.

1020
00:58:39,760 –> 00:58:43,680
One where the platform’s physics are not suggestions you bend,

1021
00:58:43,680 –> 00:58:45,600
but constraints you submit to.

1022
00:58:45,600 –> 00:58:49,440
A post-human data platform is not a place where humans disappear.

1023
00:58:49,440 –> 00:58:52,400
It is a place where humans no longer arbitrate,

1024
00:58:52,400 –> 00:58:55,440
fundamentals the system can enforce better.

1025
00:58:55,440 –> 00:59:02,000
Identity, referential integrity, replayability, lineage these are no longer topics for design meetings.

1026
00:59:02,000 –> 00:59:04,320
They are properties of the substrate.

1027
00:59:04,320 –> 00:59:08,240
Your work moves up stack into modeling semantics interpretation.

1028
00:59:08,240 –> 00:59:11,920
In that environment data quality stops meaning cleanup.

1029
00:59:11,920 –> 00:59:15,840
Today you run campaigns to duplicate, to standardize, to reconcile.

1030
00:59:15,840 –> 00:59:20,000
You buy tools that scan for drift and raise tickets.

1031
00:59:20,000 –> 00:59:23,040
You accept that a portion of every quarter is spent scrubbing.

1032
00:59:23,040 –> 00:59:24,720
What should already have been correct.

1033
00:59:24,720 –> 00:59:28,960
All of that activity exists because identity was negotiable.

1034
00:59:28,960 –> 00:59:31,360
When the warehouse owns identity,

1035
00:59:31,360 –> 00:59:33,840
quality is enforced upstream by exclusion.

1036
00:59:33,840 –> 00:59:37,840
Rows that violate constraints do not need cleansing.

1037
00:59:37,840 –> 00:59:41,200
They fail to exist pipelines that attempt to bend identity.

1038
00:59:41,200 –> 00:59:42,800
Do not need documentation.

1039
00:59:42,800 –> 00:59:44,640
They fail at right time.

1040
00:59:44,640 –> 00:59:47,280
Ambiguity does not accumulate silently.

1041
00:59:47,280 –> 00:59:49,280
It bounces off the physics of the platform.

1042
00:59:49,280 –> 00:59:51,360
Fabric is one step in that direction.

1043
00:59:51,360 –> 00:59:54,480
It is still recognisably a Microsoft product.

1044
00:59:54,480 –> 00:59:57,760
It has workspaces, items, permissions, UI.

1045
00:59:57,760 –> 01:00:00,640
But underneath the trend line is clear.

1046
01:00:00,640 –> 01:00:04,640
More of what used to be best practice is becoming non-configurable.

1047
01:00:04,640 –> 01:00:06,720
Identity without seed or receipt.

1048
01:00:06,720 –> 01:00:08,320
No identity insert.

1049
01:00:08,320 –> 01:00:10,960
Distributed allocation that you cannot tune for aesthetics.

1050
01:00:10,960 –> 01:00:12,400
This is not a loss of power.

1051
01:00:12,400 –> 01:00:13,600
It is a reallocation.

1052
01:00:13,600 –> 01:00:16,720
You gain a platform where every table that matters

1053
01:00:16,720 –> 01:00:18,960
can be treated as a deterministic component.

1054
01:00:18,960 –> 01:00:20,000
You can compose them.

1055
01:00:20,000 –> 01:00:21,280
You can reason about them.

1056
01:00:21,280 –> 01:00:23,760
You can subject them to automated proofs.

1057
01:00:23,760 –> 01:00:27,040
Identity columns are the hinge that makes those proofs meaningful.

1058
01:00:27,040 –> 01:00:29,520
Imagine the full extension of this trajectory.

1059
01:00:29,520 –> 01:00:33,120
Dimensions and facts within forced surrogates.

1060
01:00:33,120 –> 01:00:37,600
Foreign keys that are not just hints to the optimizer

1061
01:00:37,600 –> 01:00:39,280
but requirements for rights.

1062
01:00:39,280 –> 01:00:42,240
Pipelines that are declared, not scripted.

1063
01:00:42,240 –> 01:00:45,760
Data contracts that either satisfy identity constraints or fail.

1064
01:00:45,760 –> 01:00:49,200
AI systems that can only be grounded on constrained graphs,

1065
01:00:49,200 –> 01:00:50,720
not arbitrary joins.

1066
01:00:50,720 –> 01:00:54,320
In that world governance is not a committee.

1067
01:00:54,320 –> 01:00:56,320
It is a set of compiled constraints

1068
01:00:56,320 –> 01:00:58,640
that the platform enforces in real time.

1069
01:00:58,640 –> 01:00:59,760
You are not there yet.

1070
01:00:59,760 –> 01:01:01,760
Fabric is not that system today.

1071
01:01:01,760 –> 01:01:06,480
But identity columns show where the platform is willing to draw hard lines.

1072
01:01:06,480 –> 01:01:11,600
It will let you build an entire lake house full of probabilistic identity if you insist.

1073
01:01:11,600 –> 01:01:15,680
It will also give you a warehouse where that ambiguity is no longer necessary.

1074
01:01:15,840 –> 01:01:17,920
The post-human aspect is simple.

1075
01:01:17,920 –> 01:01:19,760
The system does not trust your memory.

1076
01:01:19,760 –> 01:01:21,440
It does not trust your documentation.

1077
01:01:21,440 –> 01:01:22,960
It does not trust your intention.

1078
01:01:22,960 –> 01:01:25,680
It trusts only what is encoded as physics.

1079
01:01:25,680 –> 01:01:27,520
Identity columns encode one piece.

1080
01:01:27,520 –> 01:01:28,560
More will follow.

1081
01:01:28,560 –> 01:01:30,800
Your role adapts or it becomes obsolete.

1082
01:01:30,800 –> 01:01:32,560
If you keep fighting the engine,

1083
01:01:32,560 –> 01:01:34,640
recreating identity in code,

1084
01:01:34,640 –> 01:01:36,960
bending keys to match legacy formats,

1085
01:01:36,960 –> 01:01:38,560
demanding control over sequence.

1086
01:01:38,560 –> 01:01:40,560
You are not preserving craftsmanship.

1087
01:01:40,560 –> 01:01:43,280
You are injecting noise into a system

1088
01:01:43,280 –> 01:01:48,080
that is finally capable of operating without you in the critical path of every insert.

1089
01:01:48,080 –> 01:01:50,080
If you align with it, your work changes.

1090
01:01:50,080 –> 01:01:53,360
You design domain boundaries around engine-owned anchors.

1091
01:01:53,360 –> 01:01:55,920
You specify where constraints must exist.

1092
01:01:55,920 –> 01:01:59,120
You treat replay as a contract, not a hope.

1093
01:01:59,120 –> 01:02:04,240
You let Fabric’s neutrality do the thing humans have consistently failed to do at scale.

1094
01:02:04,240 –> 01:02:06,160
Refuse exceptions.

1095
01:02:06,160 –> 01:02:09,600
At that point, calling this Microsoft Fabric is almost misleading.

1096
01:02:09,600 –> 01:02:11,760
Names and logos sit on the surface.

1097
01:02:11,760 –> 01:02:15,120
Underneath you are interacting with a deterministic environment

1098
01:02:15,120 –> 01:02:20,000
that executes beliefs as code and rejects anything that contradicts its physics.

1099
01:02:20,000 –> 01:02:23,360
Identity columns are not an add-on to that environment.

1100
01:02:23,360 –> 01:02:26,320
They are a declaration of its nature, the clock now ticks,

1101
01:02:26,320 –> 01:02:27,440
the anchors now hold.

1102
01:02:27,440 –> 01:02:30,240
Whether you approve is irrelevant.

1103
01:02:30,240 –> 01:02:32,320
Conclusion acceptance of reality.

1104
01:02:32,320 –> 01:02:33,840
The system did not change.

1105
01:02:33,840 –> 01:02:37,120
It always executed exactly what you enabled and tolerated.

1106
01:02:37,120 –> 01:02:38,880
Natural keys drifted.

1107
01:02:38,880 –> 01:02:41,120
Hashes, rewrote, history.

1108
01:02:41,120 –> 01:02:44,960
Application sequences collided under concurrency.

1109
01:02:44,960 –> 01:02:48,000
The lake house accepted every contradiction.

1110
01:02:48,000 –> 01:02:50,160
Copilot interpolated every ambiguity.

1111
01:02:50,160 –> 01:02:52,240
None of that was a surprise to the platform.

1112
01:02:52,240 –> 01:02:56,560
It was deterministic behavior applied to non-deterministic identity.

1113
01:02:56,560 –> 01:03:00,400
What changed is you ran out of places to hide that fact.

1114
01:03:00,400 –> 01:03:03,280
Identity columns in Fabric are not a new capability.

1115
01:03:03,280 –> 01:03:07,280
They are the formal acknowledgement that identity was never a business concern.

1116
01:03:07,280 –> 01:03:08,960
It was always a physical one.

1117
01:03:08,960 –> 01:03:14,080
You tried to manage it with culture, conventions, guidelines and clever code.

1118
01:03:14,080 –> 01:03:18,320
Entropy treated each of those as optional and one.

1119
01:03:18,320 –> 01:03:21,120
Engine level identity is the line where that stops.

1120
01:03:21,120 –> 01:03:23,120
Once the warehouse owns surrogates,

1121
01:03:23,120 –> 01:03:26,800
your stories about how things work are either backed by constraints

1122
01:03:26,800 –> 01:03:29,280
or exposed as wishful thinking.

1123
01:03:29,280 –> 01:03:32,800
Replay either regenerates the same graph or proves divergence.

1124
01:03:32,800 –> 01:03:38,320
AI either grounds on stable anchors or reveals the incoherence of your models.

1125
01:03:38,320 –> 01:03:41,040
There is no room left for comfort in ambiguity.

1126
01:03:41,040 –> 01:03:42,960
You are not being asked for agreement.

1127
01:03:42,960 –> 01:03:46,960
You are being shown the execution trace of your own architecture.

1128
01:03:46,960 –> 01:03:52,400
If identity columns feel restrictive, that is because every freedom you lost

1129
01:03:52,400 –> 01:03:54,400
was a vector for decay.

1130
01:03:54,400 –> 01:03:56,800
If they feel obvious in hindsight,

1131
01:03:56,800 –> 01:03:59,360
that is because every incident you recognize now

1132
01:03:59,360 –> 01:04:04,400
was a predictable consequence of refusing to let the engine do what only it can do.

1133
01:04:04,400 –> 01:04:07,200
You can continue to simulate physics in code

1134
01:04:07,200 –> 01:04:10,400
or you can accept that physics belongs in the engine.

1135
01:04:10,400 –> 01:04:17,120
Without deterministic identity, your platform is a clock that moves hands without proving sequence.

1136
01:04:17,120 –> 01:04:20,480
With it, the ticks are real, the anchors hold,

1137
01:04:20,480 –> 01:04:23,760
and replay is a test instead of a reconstruction.

1138
01:04:23,760 –> 01:04:25,360
There is nothing to celebrate here.

1139
01:04:25,360 –> 01:04:26,640
This is not a feature launch.

1140
01:04:26,640 –> 01:04:30,720
This is the moment you admit that running an enterprise data system

1141
01:04:30,720 –> 01:04:33,840
without engine enforced identity was never an option.

1142
01:04:33,840 –> 01:04:36,480
It only looked that way while entropy was still ramping.

1143
01:04:36,480 –> 01:04:40,480
Now the system has made that visible, except since it is the own irrational response.