Welcome to PASS Summit 2017!
Today, we’re pleased to announce the release of a new version of Power BI Report Server. This release contains all of the features we first introduced in the August 2017 Preview, and several new features customers have been anxiously waiting for, including support for scheduled data refresh, Direct Query, and a new REST API for developers. This is an update to the June 2017 release and is supported for production workloads, so you should feel free to upgrade your production environment to take advantage of all of these new capabilities.
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Scheduled data refresh for your Power BI reports
With the August 2017 Preview of Power BI Report Server, we introduced the capability to upload Power BI reports that didn’t require an external connection to SQL Server Analysis Services. While this enabled the ability to view those reports on the server, it didn’t yet allow you to refresh the data feeding that report.
Now, users can set data refresh schedules for their Power BI reports that are using any of over two dozen data sources. This includes all the most popular data sources customers use in the Power BI Service, including SQL Server, Oracle, Excel Workbooks, SAP HANA and many others. We have the complete list of supported data sources in the online documentation. You can even set multiple refresh schedules for each report, enabling even more control around how often you update your data.
In addition, we’ve upped the size of the files that you may upload to the server and schedule data refresh for to up to 2 GB.
Direct Query support available for Power BI Reports
For reports that always need to look at the live source data, we’ve added support for Direct Query. Direct Query is enabled in this release for the following data sources – SQL Server, Azure SQL Database, Oracle, Teradata, SAP HANA and SAP BW. Simply choose the “Direct Query” option when you’re creating your report in Power BI Desktop and load your report to the server. Once loaded, you can set the credentials used when connecting to the data source for report viewers, or if you’d like to connect as the user viewing the report to take advantage of row-level security that’s been set at the data level for certain data sources.
First introduced in SQL Server 2017 Reporting Services, a new, modern REST API for Report Server is now available. Think of it as a RESTful successor to the legacy ReportingService2010 SOAP API. It has been extended to account for the additional report types we support in Power BI Report Server.
The REST API provides programmatic access to the objects in a report server catalog: folders, reports, KPIs, data sources, datasets, refresh plans, subscriptions, and more. Using the REST API, you can, for example, navigate the folder hierarchy, discover the contents of a folder, or download a report definition. You can also create, update, and delete objects: upload a report, execute a refresh plan, delete a folder, and so on.
Connect to your shared datasets in Report Server via OData
Shared datasets in SQL Server Reporting Services have been used for years to enable the re-use of a single dataset across multiple reports and report types. We’ve extended the functionality of the new REST API to also make these datasets available for use in your Power BI reports via OData. To connect to a shared dataset in your Power BI Reports, you can use the OData data source in Power BI Desktop and connect to the proper URL for your data source. Please refer to the walkthrough in the documentation for this release for more details.
Filter a Power BI report using URL parameters
Imagine you’ve embedded a Power BI report into another app using an iframe and a URL like the following:
Now you can specify additional filters using the “filter” URL parameter:
https://reportserver/reports/powerbi/Store Sales?rs:Embed=true&filter=Store/Territory eq 'NC' and Store/Chain eq 'Fashions Direct'
The syntax is similar to one you might’ve used with the Power BI service.
To learn more about these new features, please make sure you read the release notes and supporting documentation we’ve published to the Power BI website. We’re looking forward to hearing your feedback in the comments below or in the Power BI forums.