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Microsoft Azure Synapse Analytics

Reporting should
end the argument.

Synapse brings data warehousing and big data analytics together, with real-time insight through Power BI and predictive modelling on top. We design it around the decisions you need to make, and size it so the cost stays predictable.

What it actually does

If Microsoft Fabric alone would meet the requirement more simply, we will say so before designing anything larger.

Sound familiar?

The reporting is not slow. It is disputed.

When numbers are assembled by hand from separate systems, the meeting is spent agreeing the figures rather than acting on them.

  • Two reports, two answers

    Each built from a different extract, so the meeting is spent reconciling rather than deciding.

  • The month-end pack is assembled by hand

    One person knows how, and the business quietly depends on them being available.

  • Queries run overnight, or not at all

    The warehouse was sized for a smaller company and nobody has revisited it.

  • Operational and financial data never meet

    So questions that span production, stock and margin cannot be answered in one place.

  • Forecasting is opinion with a spreadsheet attached

    The history exists, but nothing is modelled well enough to predict from.

What it actually does

Four capabilities, each with a cost decision attached.

Synapse is flexible, which is exactly why it needs deliberate design rather than defaults.

Structured and big data in one service.
Warehousing1 of 4

Structured and big data in one service.

Synapse brings enterprise data warehousing together with big data analytics, querying structured and unstructured data through dedicated or serverless SQL pools and Spark.

What this gives you

  • One platform to answer both the finance question and the operational one, without moving data between tools.
  • We decide dedicated against serverless per workload, because the wrong choice is the most common source of unexpected cost.

Swipe, drag or use the arrow keys to move between decisions.

Synapse usually sits on top of Azure Data Lake and is consumed through Power BI and Microsoft Fabric. Prediction on top of it is covered under predictive intelligence.

How we deliver it

The warehouse is the easy half.

Definitions, ownership, data quality and cost control decide whether the platform is still trusted a year later.

  • Before anything is provisioned, we agree what questions the platform has to answer and who owns each definition.

    • The decisions the business needs data to support, written down
    • Warehouse model, layers and where the source of truth sits
    • Dedicated against serverless SQL pools per workload
    • Where Synapse ends and Microsoft Fabric or a lake begins
    • A phased delivery, with a first release that proves the pattern

    If Microsoft Fabric alone would meet the requirement more simply, we will say so rather than build more than you need.

Why InteliSense

We build analytics around decisions.

A warehouse that does not change a decision is a cost centre with good documentation.

  • Decisions first, platform second

    We start from the questions the business cannot answer today, not from a reference architecture.

  • Cross-platform integration

    Dynamics 365, Power Platform, Azure and third-party sources delivered by one accountable team.

  • Sized to stay affordable

    Serverless against dedicated, pause schedules and refresh frequency are design decisions we take with you.

  • One agreed set of definitions

    Measures are defined and owned before dashboards are built, so reporting stops being contested.

  • Honest about prediction

    If your history will not support a reliable forecast, we would rather fix the history than sell a model.

  • Accountable afterwards

    Ongoing support, tuning and optimisation with named ownership, not a handover pack.

Before you call

The questions data and finance leaders ask first.

A conversation, not a demo

Start with one contested number.

Tell us which figure gets challenged every month and where it comes from. We will tell you what it would take to make it trusted, and whether Synapse is the right place to do it.

See customer stories