We are excited to announce the initial release of a query performance optimization aimed at processing Data Analysis Expressions (DAX) queries more efficiently, known as “Horizontal Fusion”.
» 阅读更多内容We are committed to helping our Azure Analysis Services customers unlock the enormous capabilities of Power BI as a superset of Azure Analysis Services through a smooth migration path to Power BI. As part of this effort, we are happy to announce today that Power BI has reached yet another compatibility milestone with the introduction of explicit Dataset Write permissions.
» 阅读更多内容Power BI APIs can support you at any scale, but there is no one-size-fits-all API. The ExecuteQueries API is a great choice at small scale. For large-scale solutions, switch to XMLA endpoints and host your datasets on Power BI Premium.
» 阅读更多内容As part of our GA work for the ExecuteQueries REST API, we delivered a new Power Automate action to run queries against Power BI datasets. This action delivers a straightforward low-code/no-code experience to BI users who want to streamline repetitive, mundane tasks and processes. The purpose of this blog post is to help you get started running queries against datasets in Power Automate. It covers exporting data into csv files, building a solution to test datasets, and creating BI-driven cloud flows.
» 阅读更多内容We are happy to announce that the ExecuteQueries REST API is now GA. By using this REST API, you can query datasets in Power BI from practically any modern environment on any platform, as long as you can authenticate with Azure Active Directory (AAD) and construct a Web request. The query functionality is comparable to XMLA read access, yet avoids dependencies on Analysis Services client libraries, requires no connection to XMLA endpoints, and works in Premium workspaces as well as in ordinary workspaces.
» 阅读更多内容Today, we are excited to announce General Availability (GA) of automatic aggregations, along with several important improvements. By using automatic aggregations in Power BI Premium, you can unlock cloud-scale data volumes for interactive analysis. Automatic aggregations import data into the dataset only at the aggregated level while leaving the detail data at the source to minimize data duplication. In this way, most BI queries can benefit from Power BI’s blazing fast query performance in import mode, while occasional detail queries can still work transparently against the data source in DirectQuery mode.
» 阅读更多内容Today, we’re happy to announce significant performance improvements to backup and restore operations for datasets in Power BI. Our benchmark tests with 1GB, 5GB, and 10GB datasets show backups can now be completed up to 22 times faster than before, and the time required for restore operations can also be reduced by more than 30%.
» 阅读更多内容We are excited to announce support for Hybrid Tables and Incremental refresh with real-time data in Power BI Premium to strike the right balance between query performance and data freshness. Now you can have blazing fast performance in import mode and the latest data changes in the data warehouse reflected in user reports without having to perform a dataset refresh.
» 阅读更多内容We are announcing support for user impersonation using the EffectiveUserName connection-string property. This is truly exciting because it opens the door for mass migrations of tabular Analysis Services solutions that rely on EffectiveUserName-based impersonation to Power BI. It also opens new options for administrative tools and scripts to connect to datasets on Power BI Premium using different user identities! Impersonating another user can be as easy as specifying that user’s UPN on the connection string.
» 阅读更多内容We are excited to announce that XMLA endpoints on Premium Per User (PPU) now support Azure Active Directory (AAD) authentication with service principals. This authentication option enables administrative applications to perform automated maintenance tasks and unattended service-level operations by using their own app identities, which is often a requirement for migration of existing tabular data models from Azure Analysis Services and SQL Server Analysis Services to Power BI Premium. For technical details, see the article Automate Premium workspace and dataset tasks with service principals in the product documentation.
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