Connection Tool - Programmatically Remove Unused Datasource Connections, and List All Connections
Managing connections within your Sisense environment can become complex over time, if there are a large number of connections, and connections are often added, and replace earlier datasource connections. In some scenarios unused connections can accumulate, potentially cluttering the connection manager UI with no longer relevant connections. Although unused connections typically represent minimal direct security risk, it's considered best practice to maintain a clean, organized list of connections, and in some scenarios it can be desired to remove all unused connections. Sisense prevents the deletion of connections actively used in datasources, safeguarding your dashboards and datasources from disruptions. However, inactive or "orphaned" connections remain after datasources are deleted or a connection is replaced, potentially contributing to unnecessary UI complexity in the connection manager UI. Connections can be of any type Sisense supports, common types include various SQL connections, Excel files, and CSV files, as well as many data providers, such as Big Panda. This tool can also be used to list all connections, with no automatic deletion of unused connections.How to create a list of users with a current role
How to create a list of users with a current role To get a list of the users with their roles you can use table usage. Get the next fields from it - email and userRole. In this table, you can find all the roles that these users had previously [ALT Text: A table displaying two columns: "email" and "userRole." The "email" column contains redacted email addresses, while the "userRole" column lists different roles such as "Viewer," "Data Designer," "datadesigner," and "Designer." Some users appear multiple times with different roles.] To avoid this, lets go to the elasticube, open table usage. Create a Custom Column [ALT Text: A screenshot of the Sisense Elasticube interface showing the usage table with multiple fields, including trackingId, timeStamp, userId, userRole, and more. An arrow points to the three-dot menu next to the usage table, where a dropdown menu is open. The "Add Custom Column" option is highlighted in red, indicating the selection for creating a new custom column.] Name it - rank_date_ids We will use the function RankCompetitionDesc (https://docs.sisense.com/main/SisenseLinux/mathematical-functions.htm) Our query will look like this: RankCompetitionDesc( email, [timeStamp] ) Press the Save button and Build the Elasticube [ALT Text: A screenshot of the Sisense Elasticube interface showing the creation of a custom column named rank_date_ids in the usage table. The formula RankCompetitionDesc(email, [timeStamp]) is entered in the editor. An arrow points to the "Save" button, indicating the action to save the custom column. The status message at the bottom confirms that the formula has been parsed successfully.] Go to the dashboard and edit our widget. Add a filter for a column rank_date_ids = 1 [ALT Text: Dropdown menu interface with multiple selectable options. Check the box next to each option. "Add Filter" and "Usage Analytics Model" are visible. One item is selected and highlighted.] As the result, we will get the current user roles for every user. [ALT Text: Table showing an email column with text obscured in red and a user-role column listing "Viewer" and "Data Designer".]
