If your investment process runs in a warehouse, the question is not whether analyst data is useful, it is how much plumbing it takes to get it next to your own tables. AnaChart’s feed answers that: a native Snowflake or BigQuery share that shows up in your account and behaves like any internal table. No ETL, no file transfer, no API to babysit.
The feed carries the full analyst price target dataset: 661,383 price targets and 759,654 ratings across 7,191 analysts and 9,686 tickers, 2004 to 2026. This page is about how it reaches your stack and joins to what you already have.
How the native share works
On Snowflake and BigQuery, a share is a live pointer, not a copy. We grant your account access and the data appears as a schema you can query immediately. When we publish new analyst actions, your view updates. You never move a file, run a loader, or version a download. Access is read-only and scoped to your account.
The fields you join on
| Field | What it is |
|---|---|
| ticker | Standardised symbol, with delisted and renamed names preserved |
| analyst_id / analyst, firm | Stable analyst key plus name and covering firm |
| action_date | Exact date each target or rating was issued or revised |
| price_target | Target at time of issue, with the previous target kept |
| rating | Standardised Buy / Hold / Sell at time of issue |
| price_at_issue | Stock price on the action date, for point-in-time work |
| met, days_to_hit | Whether the target was reached and how long it took |
| met_ratio, performance_score | The analyst’s track record on the name |
Because the record is point-in-time and survivorship-free, a backtest sees each target exactly as it stood on its issue date, including on tickers that later delisted. That is the difference between a feed you can research against and a live consensus snapshot you cannot rewind. For what the accuracy fields mean and how they are scored, see the analyst accuracy data.
No warehouse? A custom report instead
Not every team wants a warehouse share. If you just need a cut, an analyst, a sector, a date range, we run it and send a clean file. Custom one-time reports start at $149, no account required. The free Apple sample shows the format before you buy, and it needs no login at all.
How teams put the feed to work
- Join analyst targets to a holdings table to see where consensus is drifting on your book.
- Build a revisions signal from issue dates and price-at-issue, weighted by each analyst’s met ratio.
- Backtest a strategy against the point-in-time record without survivorship leaking in.
- Feed a coverage dashboard that refreshes with the share, no pipeline to maintain.
Get connected
The listings are live on the Snowflake Marketplace and Google BigQuery. To scope a share or a custom cut, book a short call or email us.
FAQ
Do I need to build a pipeline to use the feed?
No. A Snowflake or BigQuery native share appears as a queryable schema in your own account. There is no file to load and no API to maintain, and it updates as new analyst actions publish.
How do I join it to my own data?
Join on ticker and action_date. Every row is point-in-time, so it lines up against a holdings or price history table without look-ahead bias, including on delisted names.
What if I do not use a data warehouse?
Ask for a custom one-time report from $149, no account needed, or start with the free Apple sample to see the format.