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Modern data platform build

A lakehouse or warehouse on Databricks, Snowflake or Microsoft Fabric, with open table formats underneath so your data outlives the tool.

Typical timing
12–20 weeks
Engagement
Phased programme
Delivery framework
User researchDiscoveryAlphaBetaLive
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Objective

Build a single, governed data platform that brings sources together, transforms them reliably and serves analytics, data science and AI from the same trusted foundation. Open formats such as Apache Iceberg or Delta keep the data portable.

You may need this if

  • Reporting relies on spreadsheets stitched from several systems
  • An ageing warehouse is slow, expensive or unsupported
  • Data science and AI teams keep building private copies of data
How it runs

Activities, step by step

The plan follows our delivery framework. Steps that do not apply to this kind of work are left out rather than padded.

  1. 01 · User research1–2 weeks

    Data consumers

    • Interviews with analysts, data scientists and business users
    • Priority questions and reports identified
    • Latency, volume and security requirements
  2. 02 · Discovery2–3 weeks

    Architecture

    • Platform selection with costs modelled
    • Medallion or domain-oriented architecture designed
    • Ingestion, transformation and access patterns agreed
  3. 03 · Alpha4–6 weeks

    Foundation and first domain

    • Platform deployed as code with security and cataloguing
    • First sources ingested with tested transformations in dbt
    • First data product and dashboard in private alpha
  4. 04 · Beta4–6 weeks

    Expand

    • Further domains onboarded
    • Data quality checks and alerting
    • Legacy reports migrated and reconciled
  5. 05 · Live2 weeks, then ongoing

    Operate and hand over

    • Cost and performance tuning
    • Runbooks and team training
    • Roadmap for further domains and AI use

Deliverables

What you keep at the end.

  • Production data platform as infrastructure as code
  • Ingestion pipelines and tested transformations
  • Data catalogue and access controls
  • First data products and dashboards
  • Operating model and documentation

Outcomes

What it is built to change.

  • One trusted version of the numbers
  • Faster answers for analysts and the business
  • A foundation ready for machine learning and AI

Often combined with

Every engagement starts with a 45-minute working session with the SME who would own the work. No deck.

Discuss Modern data platform build