You’ve just completed the DSS & SQL course, where you encountered some typical tasks when working with SQL databases in Dataiku DSS. Here are a few of the main takeaways from this course:
- SQL datasets in DSS are pointers to database tables, therefore, they are written in the database only.
- When creating visual recipes and code recipes, you can specify a database as the storage location of the output tables.
- An SQL recipe can be executed either as a query or a script.
- When using an SQL script, DSS handles the table creation, deletion, insertion into the output table, and the automatic detection of the table schema, thereby allowing you to focus on writing the main query.
- In general, we recommend that you use the SQL query over the script, except when your SQL code has common table expressions, or when you are working with data types that are not natively supported by DSS.
- We recommend that you choose a dedicated engine, such as an SQL database engine, when you want to render charts on an entire dataset.
- You can use SQL Notebooks to quickly prototype code for querying and analyzing data, without having to write your output as new datasets in the SQL database.
Be sure to check out other Academy courses!