The Scenario
You joined the data engineering team two weeks ago. Your first task: document every SHARADAR datatable the team uses so that the next onboarding doesn't take a month. The team uses 10 different Nasdaq datasets. Nobody has written down what the columns are, which ones are filterable, or when each table refreshes. That information exists in the Nasdaq Data Link API — it's just not in any document anyone can find.
The bad version:
- Hit the Nasdaq Data Link metadata endpoint for the first datatable code, read the JSON response, figure out which keys are column definitions versus table properties.
- Copy the column names and data types into a row in a workbook. Do it again for dataset two. By dataset five, you're pasting into the wrong columns because the response structure has a slightly different nesting than you remembered.
- Try to note the refresh frequency — realize it's not in the metadata response but in a different endpoint entirely, and that "daily" means end-of-business-day for some tables and midnight UTC for others.
This was supposed to be a two-hour onboarding task. It's turning into a two-day documentation sprint.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Excel workbook. It reads the datatable codes from your worksheet, calls the Nasdaq Data Link metadata endpoint for each one, and writes the schema information — column names, types, primary keys, refresh schedule — directly into the reference rows.
Pull schema information from Nasdaq for all datatables listed in column A of my Excel sheet and fill in whether each datatable is premium, its filterable columns, and its refresh frequency
What You Get
- Column names written as a comma-separated list in the adjacent column
- Data types listed in the same order as the column names (text, integer, double, date, etc.)
- Primary key columns identified as a separate field
- Last refresh date written as a date string
- Whether the datatable requires a premium subscription flagged in a separate column
What If the Data Is Not Quite Ready
You want each column on its own row rather than as a comma-separated list
For each datatable code in column A, retrieve the Nasdaq Data Link metadata and write one row per column: datatable code in column A, column name in column B, data type in column C, whether it's a primary key in column D — repeat for all columns across all 10 datatables
You also want to flag which columns are filterable in the API
For each datatable code in column A, retrieve the Nasdaq Data Link schema and write column names, data types, primary key status, and whether the column is filterable via the API into columns B, C, D, E
One of the datatable codes might have changed — you want a note if any return a 404
For each datatable code in column A, query the Nasdaq Data Link metadata endpoint — if the datatable is not found or has been deprecated, write "Not found" in column B and leave columns C through E blank; otherwise write column names, data types, primary keys, and last refresh date
You want the full schema plus a readiness assessment in one pass
For each datatable code in column A, retrieve the Nasdaq Data Link schema and write column names, data types, primary keys, and refresh date into columns B through E — then add column F with "Production Ready" if the datatable is not premium-only and was refreshed in the last 7 days, "Premium Required" if it requires a subscription upgrade, and "Stale" if last refresh is more than 7 days ago
Document and assess in one prompt, so the onboarding workbook is immediately useful rather than requiring a manual review pass afterward.
Try It
Get the 7-day free trial of SheetXAI and open any Excel workbook with a list of Nasdaq datatable codes, then ask it to pull the full schema definition for each one from the Data Link metadata API. You can also explore the spoke on triggering bulk datatable exports or the Nasdaq overview.