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Akin to tables in a database, sources store data according to a defined schema. All the workspace data lives inside sources, which can be queried, filtered, aggregated, and joined using SQL.

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Data Formats

We support the following formats:
  • CSV
  • NDJSON
  • JSON
You may upload this data via raw text, file upload, or remote URL.

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Ingesting Data

Navigate to “Integrations” on the left menu bar, and click on ”+”:

data format options

Upload your data via your preferred format, then press “Continue”.
From here, you can verify that your data was ingested correctly and change the name if needed: verification Once you are ready to ingest the rest of your data, press “Click Integration”.

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Metrics

Within a few seconds, you should be able to see how many rows were ingested to verify that your data was processed correctly. metrics From here, “Data” displays all your data. You may also get a detailed look at each item by clicking on its individual cell: detailed view You may also use the table’s features:
  • Filters allows you to filter out certain rows based on a condition
  • Sort can be used to order your rows in ascending/descending order based on a specififed column
  • Group by is for organizing your rows by a specified column, grouping related rows together based on a shared value in that column

“Data Graph” shows any tables or queries affiliated with this source. Upon creation, you should just see the source by itself:

source by itself


“Logs” provides details on any errors that occurred during ingestion (if any). “Ingestion Example” provides the code for ingesting data that you can simply copy and paste. Available in JS, Python, and cUrl.
Now that we have our source created, we can move onto extracting insights via AI tables.
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