QlikView Bookmarks – Your Shortcut to Data Wonderland!

In QlikView, bookmarks are used to save and restore specific states of an application or document. Bookmarks can be used to save the current selections, filters, and visualizations in an application and then restore them at a later time.

To create a bookmark in QlikView, select the “Bookmarks” tab in the toolbar and then click the “Add bookmark” button. You can then give the bookmark a name and description and specify which objects and selections to include in the bookmark.

To restore a bookmark, select the “Bookmarks” tab and click on the bookmark you want to restore. QlikView will then restore the saved state of the application or document.

Bookmarks can be a useful tool for saving and sharing specific views of an application or document or for quickly restoring a specific state of an application.

In QlikView, a bookmark is a feature that allows users to save the current state of a visualization, including the selections made and the layout of the data. This allows users to easily navigate back to specific views of the data at a later time without having to manually recreate the same selections and layout.

Bookmarks can be created by the user, with the option to add a name and a description to it, making it easy to identify the saved state later on. Once a bookmark is created, it can be accessed from the Bookmark pane or from the Bookmark menu and can be applied to the current visualization, making all selections and layout changes that were made at the time the bookmark was created.

Bookmarks can also be used to share specific views of the data with other users by creating a shared bookmark that can be accessed by multiple users. Additionally, bookmarks can also be exported and imported, allowing them to be shared between different QlikView applications.

In summary, QlikView bookmarks are a useful tool for saving and sharing specific views of the data, allowing users to easily navigate back to important insights and to share their findings with others. It’s a powerful feature that can save a lot of time, especially when working with large and complex data sets.