Data Collection Explained

What you will learn

• Know which datasets are collected before the analysts start.
• Understand how stock and ETF data collection differ.
• Use the Data Collection step to judge data quality and coverage.

Core concepts

Data Collection is the first stage of committee analysis because the later analysts need a shared fact base. For stocks, the system fetches quote and price context, technical indicators, company news, social sentiment, financial metrics, financial statements, analyst recommendations, earnings transcripts, and insider activity. For ETFs, the workflow shifts toward holdings and exposure data rather than single-company financials.

This matters because every later conclusion depends on what was actually gathered. If a key dataset is missing or weak, you should treat later confidence with more caution. One of the fastest ways to become a stronger user is to inspect Data Collection before reading the memo.

The step is also a good reminder that different assets need different evidence. ETFs are not judged with the same inputs as individual operating companies.

Common mistakes

• Skipping the Data Collection step and jumping straight to the final memo.
• Assuming all asset types should have the same supporting data.
• Ignoring missing or thin data coverage.