Data mining and big data

In most institutions data is not missing, it is unreachable: it sits in different systems, in different formats, under definitions that disagree with one another. Our work here is to bring scattered sources under one set of definitions and make them answerable to questions.

Scope

• Ingestion from source systems and pipeline design
• Transformation, deduplication and a single agreed set of definitions
• Storage and archival strategy for high-volume data
• Query and reporting layer
• Data quality checks and traceability back to the source

How we work

Being able to trace every figure back to its source is a baseline requirement. If you cannot see which record a reported value came from, through which transformation and on which date, that report cannot support a decision. We build that traceability into the design rather than bolting it on later.