Suggestions for using self-service dataset

When using a self-service dataset, some operations can affect the performance of the self-service dataset.

This article will give some suggestions for using self-service datasets.

Add as few database tables directly as possible.

Since adding database tables will add all the data of a table into FineBI while using SQL dataset users can add only some of the data they need to reduce the pressure on the system.

You can add self-service datasets and other data processing operations on the basis of SQL datasets.

With more table steps, the performance of the self-service dataset may be degraded. It is recommended that users process no more than 15 step operations in a self-service dataset.

If 15 step operations cannot meet the analysis requirements, you can use a self-service dataset A to do some operations first, and then build a new self-service dataset B on the basis of A to complete the analysis next. Self-service dataset A should be set to "no data extraction", as shown in the following figure.

Intermediate self-service dataset (a table that does not need to be displayed): For example, the self-service dataset A in Section 3, which is not the final self-service dataset.

The intermediate self-service dataset is set to "no extraction setting", which can improve the performance of the self-service dataset. The problem of slow update of intermediate steps taking up a lot of space when the data volume is large is ensured.

See Section 3 of this paper.