BI Strategy & Metric Discovery
Auditing existing reports and spreadsheets, interviewing the people who use them, and agreeing on the metrics that actually drive decisions before a dashboard is designed.
Services / Data & Analytics / Business Intelligence
Same Data. Different Numbers. Not Anymore.
Every team already has reports: spreadsheets, exports, slide decks, one-off queries. Business Intelligence is how 3Shadz turns that scatter into governed metrics, clear dashboards, and self-service views that agree with each other, so a decision made from a report holds up when someone checks it later.
Business Intelligence
A dashboard with nice charts is not Business Intelligence.
It’s the discipline of defining what a metric means, once, and building the models and views that let people explore it, without redefining it every time they open a different tool.
3Shadz designs the semantic models, metric definitions, and reporting architecture that sit between your warehouse and the people who need the numbers, then builds the dashboards, reports, and self-service views on top of it. That means deciding what “active customer” or “on-time delivery” actually means before a single chart is drawn, so finance, operations, and leadership are never quietly answering different questions with the same label.
The goal isn’t a dashboard that impresses in a demo. It’s a report someone still trusts enough to open first, six months after launch, without checking the number against a spreadsheet.
Business Intelligence is one of five connected capabilities inside 3Shadz’s Data & Analytics practice, alongside Data Engineering, Data
Warehousing, Big Data Engineering, and Data Governance. Head back to all
Services to see how it fits alongside AI, Design, Software Engineering, Cloud, QA, and
Consulting.
What We Build
Business Intelligence Capabilities
Most engagements touch several of these at once: the modelling, the build, and the governance are rarely separable in practice.
Semantic & Data Modelling for BI
Building the metric and dimension layer between your warehouse and your reporting tool, so “revenue” or “churn” is calculated the same way everywhere it’s used.
KPI Framework & Metric Governance
Documenting metric owners, definitions, and calculation logic, and certifying the datasets people are allowed to build on top of.
Dashboard & Report Development
Designing and building executive, operational, and departmental dashboards in Power BI, Tableau, Looker, or Qlik, sized to how each audience actually reads a screen, not a single template stretched to fit everyone.
Self-Service Analytics Enablement
Structured workspaces, row-level security, and training that let business users explore governed data confidently, without every user rebuilding the same report from scratch.
Reporting Modernization & Migration
Moving legacy, spreadsheet-based, or single-vendor reporting onto a modern BI platform without losing the institutional knowledge baked into the old reports, and retiring the ones nobody actually opens.
Embedded & Real-Time Reporting
Embedding governed dashboards inside your own products and portals, and building near-real-time views for operational teams who can’t wait for an overnight refresh.
Beyond the Headline Number
See the Number. Then See Why.
A KPI card only tells you something moved. Dashboards are built with the hierarchy and drill paths to let someone go from that number to the reason behind it, in the same view.
Company Revenue
$4.82M
This quarter
Region: EMEA
$1.6M
−4% vs target
Store: Berlin-04
$142K
Below forecast
Root Cause
Stockouts
3 SKUs, 9 days
How We Work
From First Interview to Dashboards People Trust
The same four stages carry every engagement, whether it starts with one report or a full reporting platform.
01
Discover & Define
Audit existing reports and spreadsheets, interview the people who rely on them, and agree on the metrics and definitions that matter before opening a BI tool.
02
Model the Semantic Layer
Build the metric and dimension layer that sits between the warehouse and the dashboard, so every report calculates the same thing the same way.
03
Design & Build
Build dashboards and reports around how each audience actually makes decisions: the right level of detail for the boardroom, the floor, and the analyst’s own exploration.
04
Enable & Govern
Roll out access, documentation, and training alongside the dashboard, then track usage and retire or refine what isn’t working.
Why Reports Stop Agreeing
One Number, Not Three Departments’ Worth
Metric drift rarely comes from bad data. It comes from the same word being calculated three different ways in three different tools.
Without a Governed Layer
- Finance, Sales, and Marketing each define “active customer” slightly differently
- Dashboards get rebuilt from scratch in every new tool
- A number in a slide deck can’t be traced back to how it was calculated
- Self-service turns into self-service confusion, one export at a time
- Nobody knows which of six dashboards is still current
With 3Shadz Business Intelligence
- Every metric is defined once, in a semantic layer everyone reports from
- New dashboards reuse certified datasets instead of reinventing calculations
- Metric ownership and logic are documented alongside the dashboard
- Self-service is scoped to governed data, with access managed by role
- Usage is tracked, so unused reports are retired, not multiplied
What Good Looks Like
Reports People Open Without Being Told To
A dashboard is only worth what it replaces. We measure success by what stops happening: the spreadsheet nobody rebuilds, the number nobody has to double-check.
One Definition Per Metric
Certified datasets and documented calculation logic, so the same word means the same thing
everywhere it appears.
Refreshed on a Decision’s Schedule
Hourly, daily, or near real time, matched to how quickly the decision actually needs
the number, not a default refresh interval.
Adoption Tracked, Not Assumed
Usage is monitored after launch, so reports that stop getting opened are revised or retired
instead of quietly multiplying.
Why 3Shadz for BI
Built to Be Trusted, Not Just Opened Once
Most BI projects don’t fail at launch. They fail three months later, when the numbers quietly stop matching. Here’s what keeps ours from getting there.
One Semantic Layer, Every Report Agrees
Metrics are defined once and reused everywhere, so finance, ops, and leadership are always looking at the same number.
Designed Around How You Decide
Each dashboard is scoped to a specific audience and decision, not a generic template stretched to serve everyone.
Governed, Not Locked Down
Role-based access and certified datasets keep self-service safe without blocking people from exploring the data.
Tuned for Performance
Models and queries are optimized so dashboards load quickly at the concurrency your teams actually use.
Platform-Agnostic Tooling
We choose the BI platform and semantic layer that fit your stack and licensing, not the vendor we prefer.
One Team Across the Stack
The same team that models your metrics also builds the pipelines, warehouse, and governance underneath them.
The BI Stack We Work With
Platform-Agnostic, By Design
We choose the visualization tool, semantic layer, and delivery method that fit your constraints and existing stack, not the other way around.
BI & Visualization
- Power BI
- Tableau
- Looker
- Qlik Sense
- Metabase
Semantic & Modelling
- dbt semantic layer
- Cube
- LookML
- Power BI tabular models
- Star & snowflake schemas
Embedding & Delivery
- Power BI Embedded
- Tableau Embedded Analytics
- Looker embedded & APIs
- REST & GraphQL data APIs
- Scheduled & real-time refresh
Governance & Enablement
- Row-level & object-level security
- Workspace & access governance
- Usage & adoption analytics
- Metric documentation & ownership
- Certified dataset catalogs
FAQ
Business Intelligence: Frequently Asked Questions
Data & Analytics, under Services, is the umbrella practice covering engineering, warehousing, scale, insight, and governance. Business Intelligence is the specific discipline underneath it: the semantic models, dashboards, and reporting experiences that turn stored data into something people across the business can understand and use.
Data Engineering moves data reliably and Data Warehousing models and stores it. Business Intelligence sits on top of both: it defines the metrics, builds the semantic layer, and designs the dashboards people actually open. Most engagements involve all three, often as one continuous build.
Yes. We regularly build on Power BI, Tableau, Looker, Qlik Sense, and Metabase, and choose the platform that fits your existing stack, licensing, and embedding needs rather than defaulting to one vendor.
A semantic layer is the modelled layer between your warehouse and your dashboards that defines what each metric means once, so every report calculates it the same way. Most organizations don’t need one until reports start disagreeing, at which point it becomes the fastest way to fix it permanently rather than dashboard by dashboard.
Self-service is scoped to governed datasets and certified metrics rather than raw tables, with workspace structure and row-level security defined up front, so business users can explore and build without redefining what a metric means along the way.
Yes. We track usage, refresh performance, and query cost after launch, and revise or retire reports as questions and data change, rather than treating go-live as the end of the engagement.
Ready for Numbers Everyone Trusts?
Let’s Turn Your Reports Into One Governed Source of Truth.
Whether you need one dashboard, a semantic layer, a self-service rollout, or a full reporting platform, our Business Intelligence team can help you get there.