Connect Financial Modelling to BigQuery
Send Financial Modelling stocks, etfs, stock available tradeds and 14 more data types to BigQuery on a schedule. Filter by date. Refresh as often as every 15 minutes.
BigQuery
dataset financial_modelling
stocksetfsstock_available_tradedsstock_cik_listsstock_euronext_symbols- 12 more data types
How to connect Financial Modelling and BigQuery
5 steps. You can preview the Financial Modelling data in Coupler.io before anything reaches BigQuery.
Step 1 of 5
Connect Financial Modelling
Enter your Financial Modelling API key. You only do this once per account.
Step 2 of 5
Choose what to export
Pick the Financial Modelling data you want in BigQuery.
Show 9 more data types Show fewer data types
Step 3 of 5
Fine-tune the export
Optional settings for this Financial Modelling export.
Step 4 of 5
Connect BigQuery
Upload the JSON key file from your Google Cloud service account, then enter the dataset and table for the Financial Modelling data.
Step 5 of 5
Choose a write mode and schedule
Every run either replaces or appends the data in BigQuery. Run it as often as every 15 minutes.
Each run overwrites stocks with fresh Financial Modelling data.
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17 data types, including Stocks, Etfs, Stock available tradeds, Stock cik lists and Stock euronext symbols.
With your Financial Modelling API key, entered once when you add the connection.
Yes. Set the start date to cover the period you need.
Yes. If the table doesn't exist in the dataset you choose, Coupler.io creates it on the first run and fills it with Financial Modelling data.
Refresh the source field list in Coupler.io and select the new column. If you define the BigQuery table schema manually, add the column there too.
On a schedule you choose, from monthly down to every 15 minutes, depending on your Coupler.io plan.
Yes. Add more sources to the same data flow, for example QuickBooks or Xero, and join or append them before the data reaches BigQuery.
