Client Case Studies

Real projects, real outcomes. Here is how we have helped organizations turn underused data into measurable business results.

Insurance · United States

From two-day spreadsheets to real-time reporting with 100% data accuracy

The Challenge

The client's leadership relied on Power BI dashboards that pulled data from manually maintained Excel files. The data was incomplete, error-prone, and frequently out of sync with the source systems — so teams were never fully confident the numbers they acted on were correct. Refreshing a report could take up to two days of manual effort.

Our Solution

We replaced the fragile Excel-based flow with an end-to-end ETL pipeline on Microsoft Fabric, pulling data directly from the application database instead of exported spreadsheets. Using SQL and Apache Spark for transformation and DAX time-intelligence functions for accurate period-over-period reporting, we rebuilt the dashboards on clean, governed, real-time data — and embedded Copilot so business users could query their data in plain language.

Technology

  • Microsoft Fabric
  • SQL
  • Apache Spark
  • DAX
  • Power BI
  • Copilot

Results

3 hrs
Reporting time
down from 2 days
100%
Data accuracy
up from 70%
Real-time
Live source data
no manual exports
Self-serve
Copilot queries
plain-language access
Banking & Financial Services · United Kingdom

Granular, self-service visibility into bank performance

The Challenge

A UK bank's leadership needed to understand performance across multiple business domains, but existing reporting offered only high-level summaries. Analysts couldn't move from an aggregate figure to the detail behind it without commissioning a new report, which slowed every decision.

Our Solution

We designed a Power BI reporting suite built around drill-down and drill-through interactions, letting stakeholders move seamlessly from a top-line KPI to the transaction-level data beneath it. Carefully modelled filters give each domain its own clear, comparable view, so leadership can explore performance independently — without waiting on the data team.

Technology

  • Power BI
  • Drill-down & Drill-through
  • DAX
  • Data Modelling

Outcomes

Self-serve
Exploration
no new report requests
Multi-domain
Comparable views
across business lines
Granular
Drill to detail
KPI to transaction level
Retail · Forecasting & Supply Chain

An AI forecasting platform that sharpened accuracy and cut manual work

The Challenge

A retail client needed accurate budget and demand forecasting for the upcoming financial year, plus better supply-chain planning from historical consumption and production data. Forecasting was inaccurate, analysis was manual and slow, stock levels varied unexpectedly, and there was no system to flag anomalies or recommend actions.

Our Solution

We built an end-to-end machine-learning and deep-learning analytics platform that predicts next financial-year budget and demand, detects anomalies in sales and production data, and generates intelligent recommendations for inventory and supply-chain optimization. Data ingestion and processing are fully automated, and results surface through interactive dashboards for the business teams.

Technology

  • Azure Data Factory
  • Databricks
  • Machine Learning
  • Deep Learning
  • Power BI

Results

+38%
Forecast accuracy
−57%
Manual effort
92%
Anomaly precision
+24%
Supply-chain cost efficiency

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