The HOOK Methodology

A Simpler, More Reliable Way to Build Data Warehouses

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The hook
Methodology

The HOOK methodology is a modern approach to data warehousing and analytics that reduces complexity, improves alignment with the business, and dramatically increases delivery success.

Instead of organising data around systems, tables, or technical structures, HOOK models data around core business concepts—the real things an organisation works with every day, such as customers, products, orders, policies, assets, and employees.

By separating identity, context, and structure, HOOK creates data platforms that are easier to understand, easier to change, and far more resilient to ongoing business and technology change.

Why Hook?

  • Business-aligned by design

  • Lower modelling and engineering complexity

  • Source-system independent

  • Built for change, not fragile perfection

  • Works with modern cloud, lakehouse, and streaming platforms

  • Faster delivery with less rework

HOOK is a conceptual and logical modelling approach that fits naturally with your existing technology stack.

Business Concepts come first

Identity is separated from structure

Context is explicit and enforced

Complexity is constrained by design

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hook at a glance

At its core, the HOOK methodology is built on four simple ideas:

  1. Business Concepts come first

  2. Identity is separated from structure

  3. Context is explicit and enforced

  4. Complexity is constrained by design

These ideas are implemented through a small number of well-defined modelling constructs, described below.

  • Model the business, not the systems

    Business Concepts represent the things an organisation interacts with in its day-to-day operations—customers, suppliers, invoices, shipments, claims, accounts, and so on.

    In HOOK:

    • Every Business Concept has a clear boundary

    • Concepts are defined once, then reused everywhere

    • Reporting, analytics, and integration all reference the same conceptual foundations

    This ensures a shared language between business and technical teams and eliminates semantic drift over time.

  • Stable identity, independent of structure

    A Hook represents the business identity of a concept.
    It is not a table, not a surrogate key, and not tied to any one system.

    Hooks:

    • Are derived from business keys

    • Are stable over time

    • Allow data from many sources to connect safely and correctly

    Because Hooks are independent of structure, models can evolve without breaking downstream analytics.

  • Context that prevents incorrect joins

    A business key without context is ambiguous.
    A value like A01234 is meaningless unless you know what it identifies.

    Key Sets provide that context.

    In HOOK:

    • Every business key is qualified by a Key Set

    • Keys from different systems cannot be accidentally mixed

    • Incorrect joins are structurally impossible

    This removes a major class of data quality and reconciliation issues found in traditional warehouses.

  • Flexible structures built around stable identity

    A Frame is where descriptive, transactional, or historical data lives.

    Frames:

    • Attach to Hooks

    • Can be views, tables, or derived structures

    • Can change freely as requirements evolve

    Because identity is handled elsewhere, Frames are lightweight, replaceable, and easy to refactor.

  • Change without chaos

    HOOK deliberately separates:

    • Identity (Hooks)

    • Context (Key Sets)

    • Structure (Frames)

    This separation:

    • Reduces coupling

    • Localises change

    • Makes large platforms easier to reason about

    You can change sources, restructure data, or add new use cases without destabilising the whole warehouse.

  • Traditional data warehouses grow increasingly complex over time.
    HOOK explicitly limits complexity by:

    • Using a small number of modelling constructs

    • Enforcing consistent patterns

    • Avoiding unnecessary abstractions

    The result is a platform that scales in size without scaling in confusion.

  • Works with what you already have

    HOOK is independent of:

    • Databases

    • Cloud providers

    • Storage formats

    • Ingestion tools

    It works equally well with:

    • Data lakes and lakehouses

    • Cloud warehouses

    • Streaming architectures

    • SQL, ELT, and virtualisation approaches

    Technology choices can change without forcing a redesign of your core model.

  • Built for real organisations, not perfect ones

    HOOK is ideal for organisations that:

    • Have multiple source systems

    • Expect ongoing business change

    • Struggle with model fragility or rework

    • Need both agility and governance

    • Have limited resources

    It supports incremental delivery while maintaining long-term architectural integrity.

The Result

With HOOK, you get a data warehouse that is:

  • Easier to build

  • Easier to explain

  • Easier to extend

  • Harder to break

A platform designed for the way businesses actually change–not the way we wish they wouldn’t.