What Is a Databook in M&A Due Diligence?
In M&A due diligence, a databook is the structured set of financial exhibits (normalized P&L, balance sheet, working capital, and adjustment schedules) that a deal team builds from a target company’s raw financial data to support the due diligence report. It’s the analytical backbone underneath the final report: reviewers, bankers, and deal counsel reference the databook’s schedules directly when checking how a number in the report was derived.
Not to Be Confused With
A “databook” in electronics/semiconductor documentation is a component reference manual, and a separate sales-intelligence product uses the same word for something else entirely. In an M&A context, “databook” always refers to the financial exhibit set described above.
What’s Typically in One
- A normalized income statement, rebuilt from the general ledger with adjustments tagged and sourced
- Working capital schedules supporting the target/peg calculation
- Net debt and debt-like items schedule
- Customer/revenue concentration tables
- A tie-out schedule reconciling the databook back to the target’s trial balance
Why It Matters
The databook is what makes an FDD report defensible. Every adjustment in the report should trace back to a specific line in the databook. Building it by hand from a raw general ledger export is the single most time-consuming part of a traditional FDD engagement, which is why it’s the first thing AI-assisted tools automate.
PinpointAI generates a first-cut databook directly from your trial balance and GL upload →
