What we publish
Historical Stock Prices
Daily raw and adjusted OHLC for 50,000+ US stocks, ETFs and mutual funds.
Fund Returns
Trailing and calendar-year total returns for US funds and ETFs.
FRED Series
250,000+ Federal Reserve Economic Data series, refreshed daily.
Earnings Call Transcripts
Verbatim quarterly earnings calls for 4,500+ companies since 2005.
How we build the data
Every dataset is produced by pipelines we run ourselves. Orchestration runs on Dagster, and data is staged, modeled and tested with dbt in Snowflake before it reaches the secure views you query. Each dataset page documents its sources, refresh schedule and quality checks. The checks include:- Unique grain checks, so every row is exactly one security, series or date.
- Placeholder and bad-value detection, so zero or sentinel prices don’t reach the views.
- Restatement handling, so values that change after the fact, like adjusted prices after a split or dividend, are refreshed rather than left stale.
How we write our guides
Our blog answers practical questions about working with financial data in Snowflake. Every article follows the same standards:- One question, answered up front. The first paragraph answers the question in the title. The rest of the article is supporting detail.
- Facts about our data match our documentation. Coverage counts, refresh times and column definitions come from the dataset pages and the pipelines behind them.
- Competitor details are checked and dated. When we compare listings, we check each one against its own Marketplace page and documentation, say when we checked it, and mark anything we couldn’t confirm as “not listed”.
- We say when we’re comparing our own product. Comparisons that include a Fruit Stand listing say so.