Data & Analytics
Business Intelligence Implementation
Turn scattered data into decisions you can defend.
- Typical timeline
- 6-12 weeks depending on sources and metric scope
- Category
- Data & Analytics
- Engagement
- Fixed-scope phases
- You receive
- Code, data & documentation
Overview
Business intelligence is less about tools than about agreement: what a metric means, where it comes from, and who can see it. We set up a reporting layer with defined metrics so that analysis stops being a debate about data and starts being a discussion about decisions.
Every question about the business needs a project
Answering "which products are most profitable by region" means asking someone to extract data, combine spreadsheets and build a pivot table. Managers therefore stop asking, and decisions get made on instinct while the data sits unexamined.
You will recognise this if
- Any new question requires a developer or analyst to prepare data
- Two departments present different numbers for the same metric
- Analysis stops at what the standard reports happen to show
- Profitability by product, customer or region is genuinely unknown
What you get out of it
The difference this makes
Self-service answers
Managers explore and filter data themselves, which means more questions get asked and better decisions get made.
Metrics defined once
Agreed, documented definitions computed in one place remove the recurring argument about whose number is correct.
Profitability made visible
Margin by product, customer, region and channel is often the single most valuable thing a BI project reveals.
Governed access
Row-level permissions let you open up analysis without exposing sensitive data to the wrong people.
What we build
- Discovery of the decisions the business actually needs to support
- Dimensional modelling of a reporting schema separate from transactional tables
- A metric layer with documented definitions and calculation logic
- BI tool setup: Metabase, Power BI or Superset, with embedding where needed
- Curated dashboards for each function, plus self-service exploration
- Row-level security so access follows role and region
- Scheduled refresh with freshness indicators on every dashboard
- Training so your team can build their own views
- A data dictionary documenting every field and its source
How it gets used
A retail chain analysing store performance
Sales, margin, footfall and stock turns compared across stores and categories, with each manager seeing their own location.
A distributor reviewing customer profitability
Revenue, discounts, scheme cost and servicing effort combined to show which accounts actually make money.
A services firm examining delivery margins
Project revenue against time logged and cost to serve, revealing which kinds of engagement are worth pursuing.
Technology we typically use
You do not need to care about this list — but your next developer will.
- Metabase / Power BI / Superset
- PostgreSQL
- dbt
- Python
- Scheduled pipelines
Timeline: Typically 6-12 weeks depending on sources and metric scope
Questions
Business Intelligence Implementation — common questions
Something else on your mind? Ask us directly — it is usually faster than reading.
Which BI tool should we use?
Can we start small?
Do we need a data team to maintain it?
Related services
Businesses that need this often need one of these as well.
Thinking about business intelligence implementation?
Tell us about your situation. We will tell you whether this is the right service, what it would involve, and roughly what it would cost.