M&A Intelligence Platform – Unified Analytics on Databricks

Project Overview

This project simulates a real-world post-merger analytics challenge where a mature consumer goods company, AtliQon (sports equipment manufacturer), acquires a fast-growing startup, Sportsbar (nutrition & energy bars).

AtliQon operates on a stable ERP-driven OLTP + OLAP ecosystem, while Sportsbar’s data exists across cloud APIs, spreadsheets, and relational databases with no centralized analytics layer. Leadership wanted fast, reliable, cross-company insights—without committing to a multi-year data migration.

Business Problem

Incompatible data structures across two companies

No unified view for finance, sales, marketing, supply chain, and executives

Manual Excel-based reporting causing delays and inconsistencies

Need for daily automated insights post-acquisition

Solution

I designed and implemented a Databricks Lakehouse architecture that unified both companies’ data into a single analytical layer while preserving each company’s operational independence.

Key solution components:

Built an end-to-end Medallion Architecture (Bronze, Silver, Gold) in Databricks

Ingested Sportsbar’s OLTP data via AWS S3 → Databricks

Integrated AtliQon’s curated Gold-layer data directly into the Lakehouse

Performed 5-month historical backfill (July–November) with incremental daily loads from December onward

Created denormalized Gold views using SQL for BI consumption

Orchestrated automated daily pipelines with structured folder management

Enabled executive Q&A and exploratory analysis using AI Genie

Delivered multi-stakeholder dashboards covering Finance, Sales, Marketing, Operations, and Leadership

Key Insights

Revenue Synergy: December revenue peaked at $21.77B, validating successful post-merger data consolidation.

Channel Opportunity: Retail contributes 78% of revenue, while Direct & E-commerce (~20%) show strong expansion potential inspired by Sportsbar’s startup model.

Product Strategy: Core sports equipment dominates revenue, while nutrition products show high-growth cross-sell opportunities to existing customers.

Business Recommendations

Inventory Cross-Optimization: Co-locate equipment and nutrition SKUs to reduce last-mile delivery costs.

Customer Loyalty Integration: Launch a joint loyalty program leveraging the 66% new customer acquisition rate.

Process Automation: Extend orchestration to trigger real-time low-stock alerts across both companies.

Impact

Delivered a single source of truth for post-M&A decision-making

Reduced manual reporting dependency

Enabled leadership to make data-driven integration decisions within weeks instead of years

Demonstrated end-to-end ownership across data engineering, analytics, and business strategy