Held in Amsterdam, 27-29 March 2019, Power Platform Summit delivers the can’t-miss annual conference for users of the Microsoft Power platform – featuring education on Power BI, PowerApps, and Microsoft Flow.
» 阅读更多内容 In this week’s webinar the Report Server team will answer your questions about paginated reports for Power BI Report Server AND show you the answers live. Don’t have any questions? Not to worry we will have the team pull out their favorite demo and show why you should start using paginated reports now.
» 阅读更多内容 The new modeling view in Power BI Desktop is designed to work with enterprise datasets that grow in complexity
» 阅读更多内容 Happy 20th birthday Analysis Services!
» 阅读更多内容 We are happy to announce that we have just released the November update for the On-premises data gateway (version 3000.0.155.1) &…
» 阅读更多内容 We would love to hear feedback from BI Engineers and Analysts about their role and Power BI! If you’d like to provide feedback to the product team that will help inform the future of Power BI, please take this 5 minute survey! Thanks for taking to time to respond!
» 阅读更多内容 Dataset size and dataset count in memory are now available in the app
» 阅读更多内容 At Microsoft, our mission is to empower every person and every organization on the planet to achieve more. Power BI makes it possible for every employee in an organization to make better decisions based on data with beautiful reports and dashboards.
» 阅读更多内容 We have a massive Power BI Desktop update this month. Composite models, which allow you combine direct query and import sources together in one model, is now generally available. Two of the top feature requests on UserVoice, expand/collapse on the matrix and copy and pasting visuals between Desktop files, are also shipping this month. We are previewing a completely revamped filter pane that is highly customizable and have a ton of other product updates as well!
» 阅读更多内容 We’re excited to announce the availability of two new query histogram distribution charts. One is bucketed by query durations(ms) and the other is by query wait times(ms). Query histogram…
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