Data Schema vs. SQL Views

When connecting your database to datapine you may choose between pulling your whole database structure including all or only selected tables and fields or importing a prepared SQL View into datapine. Connecting your data using a SQL View can be beneficial especially if you have very large and complex data schemas.


A SQL View is thereby a virtual table based on a SQL statement that allows you to run various pre-aggregations or calculations on your data before importing it into datapine. This option allows you to select only certain columns and rows that you wish to connect to datapine and therefore limit the data set that users in datapine can query.


Here is quick comparison of why it might be useful to put your metrics into a SQL View before connecting your data to datapine.


Connect a SQL View if…


– Your database is very complex and slow


– You only need a predefined result-set that you wish to access in datapine


– You wish to limit the permissions that users will have in datapine


Import your Full Data Schema if…


– You need to access all the information stored in your database


– You don’t want any limits in terms of dashboard interactivity and filters