Rate My Financial Data Stack (for Algo Trading Potential)

Hey folks, I’m putting together a financial data stack with the goal of eventually prototyping trading bots / algorithmic strategies. I’d love your thoughts on whether this stack is solid, overkill, missing something, or just plain misguided.

Here’s what I’ve got so far:

• Historical OHLCV daily (20+ years)
• Quarterly fundamentals (15 years): balance sheet, cash flow, income statement
• Earnings call transcripts with sentiment scoring (15 years)
• Insider transactions, split into executive groupings (15 years)
• Company profiles on all symbols
• FRED data: commodities & macroeconomic indicators (50+ years)

My questions for you:

• How viable is this stack for building a trading bot?
• Which data sources are most likely to add real predictive power vs. noise?
• What would you add/remove if you were designing a stack for algorithmic trading?
• Any advice on feature engineering or modeling approaches that pair well with this kind of dataset?

I’m especially curious how people weigh fundamentals vs. sentiment vs. macro data in practice. Appreciate any feedback, critiques, or war stories from your own builds!