Data strategy and governance
Start with the commercial question. Agree the definitions. Then design the roadmap, the owners and the quality rules so finance, sales and operations stop arguing about whose file is right.
Read the serviceData strategy · Governance · Enterprise AI
Executive data strategy, master governance and enterprise AI
We help leadership teams agree what the numbers mean, put owners and quality rules on the data behind them, and then put conversational AI and Power BI on Microsoft Fabric, Databricks, AWS, Azure and Snowflake.
Data strategyMaster dataUnity CatalogDatabricks GeniePower BI Direct LakeMicrosoft FabricAWS GlueSnowflake Cortex
Data strategyMaster dataUnity CatalogDatabricks GeniePower BI Direct LakeMicrosoft FabricAWS GlueSnowflake Cortex
From source system to a decision the board can use
Four stages. Click any one for how the work actually looks.
What we actually do
Three services. The platform comes after the question is clear.
Enterprise AI you can take to production
Databricks Genie and similar tools only after the tables are certified. A chatbot on a raw extract is a demo. An answer that finance can audit is a product.
Read the servicePower BI that stays in use
Fewer pages. Clear ownership of each measure. Direct Lake in Microsoft Fabric when Friday must be on the screen on Monday.
Read the serviceThe stacks we work in
We do not arrive with a preferred logo. We work in the platform you already chose.
AWS
S3, Glue, Lake Formation, Redshift and Bedrock.
Azure and Fabric
OneLake, Synapse, Purview and Power BI Direct Lake.
Databricks
Lakehouse, Unity Catalog and Genie on certified tables.
Snowflake
Secure sharing, Snowpark pipelines and Cortex.
Align engineering with the commercial question
Programmes stall when pipelines are built away from the people who own the P and L. We sit with leadership first, write the definitions they will actually defend, and only then shape the lakehouse, the domains and the delivery plan.
Master data and active governance
Customer, product, supplier and chart of accounts should not live in five versions of Excel. We put master records, schema rules and automated quality checks inside the platform you already run: Unity Catalog, Microsoft Fabric or Snowflake. The catalogue is not a side project.
A roadmap a board can read
The output is not a 60 page deck. It is a short sequence: which decisions get a trusted number first, who owns each domain, what gets built this quarter, and what waits.
Conversational AI on certified tables
We set up Databricks Genie and similar natural language interfaces so executives can ask a question in plain language and get an answer from a table that already has an owner, a definition and tests. The query runs against the catalogue. It does not invent a metric.
What we will not do
We will not put a chatbot on a raw dump and call it transformation. If sales, finance and operations still disagree on the customer count, the first job is the definition, not the model.
A roadmap that can be audited
Use cases are ranked by whether the underlying data is ready. The first live space is small, limited to certified domains, and designed so a risk or finance lead can see exactly which table answered the question.
Microsoft Fabric and Direct Lake
Where the grain and the freshness justify it, Power BI reads Delta tables in OneLake through Direct Lake. That removes the Sunday refresh and lets leadership inspect a large set without waiting for a scheduled dataset.
Fewer pages, owned measures
We cut the report pack down to the decisions it is meant to support. Each measure has an owner. Self-service sits on the same semantic model as the board pack, so the two views cannot drift apart.
Reporting and conversation together
The visual and the natural language question should hit the same certified model. That is how a director can click a page or ask Genie and still get one answer.
Work in the platform you already chose
We do not arrive to rip out last year's decision. If Glue, Fabric, Databricks or Snowflake is already in place, that is where the pipeline, the catalogue and the consumption layer get finished.
Vendor-neutral architecture
The design should still make sense if a second cloud appears. A new operational source should not need a six month exception process before a trusted table exists.
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KPSDATA LIMITED
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08955806
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77 Whitehills Road, Loughton, IG10 1TU, UK
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+44 7908 667190
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