This Flow extracts data from file(s) and loads it into a relational database.
Extract data and load it into a database
Access Connections here.
Step 1. Create a source Connection for the file storage. Test it if possible.
- Amazon S3
- Google Cloud Storage
- Microsoft Azure Storage
- Server Storage
- Google Drive
- OneDrive for Business
- Inbound email
- Outbound email
Step 3. Create a Format for the source file. For example, use a CSV Format.
In Explorer (optional)
Acess Explorer here.
If source or destination files are nested, learn how to work with nested datasets.
Access Flows here.
Step 4. Create a new
File to database Flow.
Step 5. Add a new transformation and select
FROM Connection, Format, and filename or a wildcard filename and
TO Connection and table.
Step 6. Click
MAPPING and optionally configure the flattening for the nested JSON or XML. Most likely, it is going to be a Source SQL.
Step 7. Test the transformation. Make sure it returns the flat data set.
Step 8. Add the per-field Mapping if needed.
Step 9. If you entered a wildcard filename in
FROM, enable processing of all files which match the wildcard.
Read more about processing files matching a wildcard file name.
Step 10. Configure
MERGE (UPSERT) if needed.
Step 11. Save the Flow and execute it manually.
Step 12. Schedule the Flow to be executed periodically.