Blog August 7, 2026

Mastering M&A: How Power BI & Microsoft Fabric Streamline Acquisition Data

During a merger or acquisition, understanding the true financial and operational health of a target company is critical. Yet, traditional due diligence often drags down the deal team. Target companies typically assemble static data rooms filled with dense financial reports, projections, and hundreds of disconnected spreadsheets.

When two companies attempt to compare performance, they run into significant friction:

Incompatible KPIs: Terms that sound identical often rely on completely different underlying logic, conditions, and datasets.
Mismatched Units of Measure: One entity tracks inventory by the unit or box, while the other tracks by weight (e.g., kilograms).
Disparate Charts of Accounts: Financial systems rarely align naturally between two distinct businesses.

In a recent episode of It’s The End of The Week, Yves and Stephan discussed how leveraging modern Business Intelligence (BI) tools, specifically Power BI and Microsoft Fabric, transforms both pre-acquisition due diligence and post-acquisition integration.

Here is how a BI-first approach solves the most common M&A data challenges.

1. Streamlining Due Diligence: One-Time Data Ingestion

Instead of manually translating a target company’s reports into your own models, you can perform a one-time data load into a dedicated database linked to Power BI.

By ingesting the raw source data rather than relying on static summary files, you avoid the heavy lift of setting up automated, recurring data pipelines during the evaluation phase. Once the historical raw data is loaded, you can apply your existing internal KPI definitions and targets directly onto the target company’s metrics.

This allows your team to:

Verify financial statements against raw operational data.
Slice and dice performance instantly across customers, product lines, regional markets, sales reps, and margins.
Identify true performance trends without requesting endless custom Excel reports from the seller.

2. Resolving Data Inconsistencies with Conversion Tables

A major bottleneck when evaluating two product catalogues or operational footprints is the lack of standardized attributes. Product IDs, descriptions, and supplier codes rarely match. Furthermore, differences in units of measure (UOM) can severely skew performance analyses.

Using intermediate SQL conversion tables within Power BI, you can bridge these gaps seamlessly. For example, if a target company records inventory in cases or individual units while your framework measures by weight, an intermediate translation layer calculates conversions automatically. This normalizes the dataset without altering the underlying source files, giving you a clean, apples-to-apples comparison.

3. Post-Acquisition Integration: Day-One Visibility Without an ERP Overhaul

Once the deal closes, the immediate focus shifts to post-acquisition integration. However, forcing a full accounting system migration or ERP rollout on Day 1 is often unrealistic and disruptive.

By utilizing Microsoft Fabric and Power BI, companies can create an intermediate data layer using translation mapping tables. Even if the chart of accounts differs significantly between the parent company and the acquired entity, mapping rules ensure accounts receivable, payables, and general ledger accounts roll up into the correct consolidated categories.

This approach delivers two immediate benefits:

Aggregated Reporting on Day 1: Leadership gains full visibility into aggregated performance across all legal entities, with the ability to filter by individual entity or view combined totals.
Operational Continuity: The acquired business can continue running on its existing software while the long-term system architecture and ERP integration strategy are finalized.

Moving Beyond Excel Chaos

Relying on manual spreadsheet manipulation during an M&A process introduces delay and unnecessary risk. Applying modern data warehouse structures and business intelligence tools to target datasets brings clarity to due diligence and stability to post-merger integrations.

Whether you are currently assessing an acquisition target or working through post-deal integration, unifying your data architecture ensures you make decisions based on clear, reliable insights.

Have questions about structuring your data architecture for an upcoming acquisition? Reach out to our Business Intelligence team at LIDD to learn more.