00 · source
Data consultancy · Hampshire, UK · working worldwide
AGC Analytics covers the whole data journey: getting data out of the systems it lives in, shaping it into numbers people trust, and turning those numbers into decisions. Every step is explained in a way the room can follow, whoever is in it.
01 · pipeline
Most data work gets passed between specialists, and things get lost at every hand-off. AGC Analytics covers all three stages, so the person building your pipelines understands the questions they need to answer.
End-to-end delivery across ingestion, transformation and consumption. The same engineer owns the load, the model and the analysis, so decisions about granularity, latency and definitions are made with the downstream use in mind.
01 / 03
ingest + storesources → warehouse
Getting your data out of the systems it lives in and into one place you can rely on. Pipelines that run when they should, recover when something fails, and make it obvious when they need attention.
Ingestion from operational systems, files and APIs into a warehouse or lakehouse. Orchestrated, consistent loads with monitoring and alerting, so a failed run is visible and safe to re-run.
02 / 03
model + testraw tables → trusted models
Turning raw tables into a small set of agreed definitions (what counts as a customer, a sale, an active account) so every report starts from the same numbers.
Medallion architecture under version control: Bronze (raw ingestion), Silver (cleansing and normalisation) and Gold (curation and aggregation into marts), with data tests, documentation and lineage. Shared metric definitions, reviewed changes, and known impact before anything ships.
03 / 03
answer + decidemodels → decisions
Answering the questions the business is actually asking, and presenting the answer so the people deciding can act on it: what the numbers say, what they mean, and what to do next.
Exploratory analysis on the modelled layer, dashboards and self-serve reporting where they earn their keep, and written findings that state assumptions, caveats and the recommended action.
02 · interface
Data problems are rarely only technical. They get solved when engineers, analysts and leadership understand what is happening and why. That means strong working relationships at every level, and saying things clearly to whoever is in the room.
Finance and Sales were counting some customers more than once, in different ways. There is now one agreed definition of a customer, fixed at the source, with a check that stops it drifting again. Both reports show the same number.
fct_revenue joins orders to accounts at contract level, but the sales dashboard joins at site level, so multi-site accounts are counted once per site. Fix: conform on a single dim_account, add a uniqueness test on account_id, and repoint both dashboards.
relationshipsclaritycollaborationrigour03 · plan
From the first look at your data to something that pays its way.
Understand what you have: the systems, the data, the reports people rely on, and the places where the numbers stop adding up.
Audit sources, pipelines, models and downstream consumers. Profile data quality, trace lineage, and find where definitions diverge.
Fix what's broken first, so people can trust today's numbers while the longer-term work happens.
Triage and fix the highest-impact issues first: failing loads, broken joins, untested logic and conflicting metrics.
Build the solution that fits your business, sized for what you need now and able to grow with you.
Agree the target architecture and modelling standards, then deliver incrementally with tests, documentation and CI.
Judge the work by what changes for the business, not by how much was built.
Agree success measures up front and design for meaningful business value. Hand over with documentation your team can own.
04 · overview
05 · output
Send a few lines about what you're working with and what you need to know, by email or with the form. You'll get a reply about whether AGC Analytics can help and what a sensible first step would be.
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