Eventhouse No-Code table creation and editing
Creating and managing tables in Eventhouse just got even more flexible.
While you can create tables using the Get Data wizard – which builds the structure based on a sample file or streaming data – there are times when you need to start from scratch. This could be during basic training, testing, or experimenting with the product when you might not have sample data readily available. In these cases, building a table manually from the ground up is ideal.
The new no-code table creation experience allows you to define a table’s structure by specifying the columns and data types – no sample data, no complex KQL queries, and no technical expertise required.
Once your table is created, the edit experience allows you to:
- Rename the table or any of its columns.
- Add descriptions to the table or columns for better clarity.
- Add or remove columns to modify the structure as your needs evolve.
This flexible, intuitive UI lets you customize your table while maintaining full control over the schema.
Note: If your table already has data flowing into it, or if it has dependencies such as functions, materialized views, or ingestion mappings, editing the table structure can potentially disrupt these connections. So, be sure to use the edit functionality carefully.
Renaming the source table of a materialized view:
If the table you’re renaming is directly referenced in a materialized view, the UI will allow you to rename the table, and all materialized views that reference the old name will be updated to point to the new name in a transactional way.
However, if the materialized view references the table indirectly via a stored function, the materialized view won’t be updated automatically – you’ll need to manually update the materialized view to reflect the changes.
Whether you’re setting up a new table or refining an existing one, Eventhouse provides the flexibility you need to customize your data schema in an intuitive, user-friendly interface. Perfect for both new users and experienced data professionals alike.
To learn more about Edit a table schema, refer the documentation.
