Analytics & BICase study
Excel to Power BI Migration
An end-to-end Power BI platform that replaced Excel reporting across more than ten business units, with automated data from six formats.
Before
- Excel reports in every business unit
- One person consolidating 10+ units' reports by hand
- Errors from heavy manual intervention
- Poor data governance
After
- An automated, end-to-end Power BI platform
- A scalable semantic model
- Customisable, role-based dashboards
- Forecasting of passenger numbers and revenue
01 · The challenge
Where they started
An international airport runs multiple business units, each with its own applications, SaaS and legacy, holding data in structured and semi-structured formats.
Siloed reporting
Each business unit had its own subject matter expert producing Excel reports.
A manual bottleneck
One person consolidated reports from 10+ business units into executive dashboards.
Error-prone
Heavy manual intervention caused inconsistent, error-prone reporting.
Weak governance
Poor data governance and limited analysis in Excel at large data volumes.
02 · The solution
What we built
Our consultants learned the operational workflow and designed a data strategy to consolidate and visualise data from every business unit.
How it fits together
- 10+ business unitsSaaS and legacy apps
- 6 data formatsExcel to JSON
- Automated ingestionCleansed and centralised
- Semantic modelOne version of the truth
- Power BIExecutive and team dashboards
Every source, every format
Data from SaaS and legacy applications in Excel, SQL, Oracle, CSV, XML and JSON.
Automated ingestion
Data is cleansed, transformed and centralised without manual steps.
Semantic layer
A scalable data model serves as one semantic layer for the whole organisation.
Interactive Power BI
Static Excel reports replaced with interactive reports and dashboards.
Role-based access
The right people see the right data.
03 · Delivery
How we delivered it
- 1
Understand
Mapped each business unit's workflow, applications and reports.
- 2
Consolidate
Extracted and centralised data from every source and format.
- 3
Model
Built the scalable semantic layer and automated ingestion.
- 4
Enable
Delivered dashboards, set up access and trained staff.
04 · Results
What changed
Error-free reporting
Consistent reporting across the organisation.
New kinds of analysis
Including forecasting future passenger numbers and revenue.
Customisable dashboards
Staff create dashboards for their own role and needs.
Better data access
Staff easily find and understand the data they need.
Trained, self-sufficient staff
Power BI training and a process for regular updates.
05 · Technology
Built with
- Power BI
- Semantic model
- Oracle
- SQL
- Automated ingestion
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