Data engineering
Data Analytics & BI
When two departments arrive at a meeting with different revenue figures, the problem is rarely the spreadsheet. It is that no one agreed what the metric means or where it comes from. We fix the definition and the pipeline, then build the dashboard.
Data work fails predictably: reports assembled by hand each month, definitions that differ by department, dashboards that go stale, and a single analyst who is the only person able to answer a question. The cost shows up as decisions made late, or on instinct.
We build the unglamorous layer that makes reporting trustworthy — reliable ingestion, a modelled warehouse, tested transformations and documented metric definitions — and then the dashboards on top, which are the easy part once the foundation is right.
Capabilities
What Data Analytics & BI covers
One version of the numbers, current enough to act on.
Data warehouse design
A modelled warehouse on PostgreSQL, BigQuery, Snowflake or Redshift, structured for the questions your business asks repeatedly.
ETL & ELT pipelines
Scheduled, monitored, restartable pipelines pulling from your applications, databases, SaaS tools and partner feeds.
BI dashboards
Power BI, Looker Studio, Metabase or custom dashboards designed for decisions rather than for the density of the chart grid.
Metric definitions
A governed metric layer where every number has one written definition and one calculation, agreed across departments.
Self-service analytics
Governed datasets and training so managers can answer their own questions without joining the analyst's queue.
Data quality monitoring
Automated tests on freshness, volume, uniqueness and referential integrity, with alerts before a stale number reaches a board pack.
Why it works
What you get that you might not expect.
These are the commitments clients tell us mattered most once the project was underway.
Numbers that reconcile
Warehouse figures tied back to source systems and validated, so finance and operations stop arguing about whose report is right.
Reporting time reclaimed
Manual monthly assembly replaced by pipelines — typically several days of skilled time returned every month.
Alerting, not just charts
Thresholds and anomaly alerts that reach the right person, rather than dashboards nobody remembers to open.
Documented and portable
Version-controlled transformations and documented models your own analysts can extend without reverse-engineering.
How we deliver
Our data & bi process
Every stage produces something you can look at, use or disagree with. Nothing is invisible until the end.
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1
Decision mapping
Which decisions need better information, who makes them, how often, and what evidence would change them.
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2
Source audit
Every system holding relevant data, its quality, its refresh cadence and how it can be accessed reliably.
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3
Model & build
Warehouse schema, transformation layer with tests, and orchestration with retry and alerting behaviour.
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4
Visualise
Dashboards designed to answer the mapped decisions, reviewed with the people who will actually use them.
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5
Enable & maintain
Training, documentation and a maintenance agreement covering pipeline health and new data sources.
Proof
This service, in production.
Kalyan Threads (apparel retail, India & GCC)
One stock position across web, app, marketplaces and 24 stores
An apparel retailer with 24 stores, a website and three marketplace channels held separate stock counts on each. Oversells, buffer stock and reconciliation...
Precision Components Ltd (auto components, Coimbatore)
Raising OEE 14 points by making the shop floor visible
A components manufacturer recorded production on paper and entered it days later. Nobody could see the current shift. We connected the machines and built t...
Technologies we use for this
Chosen per project rather than by house policy. We will explain the trade-off in plain terms before anything is decided.
Questions
Data Analytics & BI — your questions
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Services that pair with Data & BI
Thinking about data analytics & bi?
Tell us the problem. You will get a rough cost, a rough timeline and an honest view on whether it is worth building — before anyone talks about a contract.