Power BI’s new "Explore This Data" feature is a game-changer for data interaction in reports. This feature with Greg Trzeciak enables users to explore data in reports without making permanent changes, allowing for a more flexible and efficient data analysis experience.
The "Explore This Data" feature is available in three locations within the Power BI service:
In the video, Greg demonstrates how this feature works in a typical Power BI report, focusing on a manufacturers analysis dataset as an example. To access the feature, users simply click on the binocular symbol (the icon for "Explore This Data") located within the report. Upon clicking, a pop-up window appears, displaying existing filters and informing the user that the feature is in preview mode.
Once inside the "Explore This Data" section, users can build custom data visualizations. The feature offers two main options:
Greg demonstrates how to manipulate the data by selecting different fields, such as "Year" and "Sales." The interface allows users to filter, rearrange, and drill down into the data, similar to the Power BI desktop experience. Users can also apply filters to the data, enabling them to narrow down the information, for example, by only displaying data before a certain year.
One of the benefits of "Explore This Data" is that users can save their explorations or visualizations. There are two main saving options:
However, Greg points out a limitation: If users want to share their explorations with others, they must ensure that the recipients have the appropriate permissions, including access to the semantic model and the necessary build permissions.
The "Explore This Data" feature provides significant flexibility in exploring and visualizing data without altering the main report. This is particularly useful when users need to ask ad-hoc questions or experiment with different visualizations without worrying about disrupting the primary data set.
However, there are some limitations to keep in mind. As mentioned, sharing explorations requires the recipient to have the appropriate permissions. Additionally, saving an exploration is only possible in specific environments, such as premium workspaces or fabric-enabled setups.
Despite these limitations, Greg is enthusiastic about the "Explore This Data" feature. He compares it to a “safari” for your data, allowing users to freely explore their datasets without worrying about making permanent changes. If you're not using this feature yet, Greg strongly recommends giving it a try for a more dynamic and flexible data exploration experience.
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