So you got an AI budgeting system and the forecasts are all over the place? Yeah, that's usually a data problem.

Mixing Different Data Sources Without Cleaning Them

You're pulling from accounting software, spreadsheets, and bank feeds. Each formats numbers differently. The AI sees $1,000 from one source and 1000.00 from another as potentially different things. Clean and standardize everything first.

Incomplete Historical Data

You need at least 12-18 months of complete data for decent predictions. Gaps mess with pattern recognition. Missing a few months? The system will either skip them or make wild guesses to fill in blanks.

Not Tagging Anomalies

That one-time equipment purchase for $50,000? If you don't flag it, the AI thinks you spend that every quarter. Mark unusual transactions so the system knows they're outliers.

Ignoring Seasonality Markers

Retail businesses have holiday spikes. Consulting firms have slow summers. Tell your system about these patterns instead of letting it figure them out from scratch.