Earlier today, Microsoft introduced the ability to embed paginated reports in applications for Power BI Embedded. The tech giant has also unveiled more additions to its data visualization service in recent days at its ongoing Ignite 2019 conference.
Last month, Power BI Dataflows received improvements in the form of enhanced compute engine refinements, non-admin gateway support, and more. Now, Microsoft has detailed a bunch of other features that have been brought to Dataflows in recent weeks.
To start off, seven new data connectors have been added to the service. They can be found in the Power Query Online Get Data experience as shown in the image above. Further detail on each of these has been provided as follows:
- PDF Files – This connector allows users to extract tables from PDF documents.
- Folder – Use this connector in order to ingest data from files in local (or network-based) file systems, or to query and analyze files’ metadata.
- SharePoint Folder – Similar scenarios as the previous item, but available on top of a SharePoint folder (either on-prem or SharePoint Online).
- Google BigQuery – Ingest data from Google BigQuery databases, transform, filter and reshape this data as part of your dataflow.
- HDInsight Spark – Read tables from HDInsight Spark databases.
- Apache Spark – Read tables from any Apache Spark distribution database, either on-prem or cloud-based.
- Generic ODBC – Plug in any ODBC driver, specify a connection string or DSN and connect from your dataflows to import and transform data from many different sources.
Over 40 new data transformation capabilities have also been introduced. These have been expressed through the following umbrella terms:
- Combine Files UX
- Merge Queries – Visual join kind selection
- Additional Number/Date/DateTime/Duration transformations UX
- List transformations: Statistics, Sort, Keep/Remove/Reverse items
- Fill Up/Down
- Move Columns left/right/beginning/end
- Replace Errors
There are also a few new Power Query authoring enhancements outlined below:
- Data Profiling
- Query Parameters UX
- Function Authoring UX
- M Intellisense support in Advanced Query Editor & Formula Bar
- Select Related Tables as part of Get Data UX
You can read in much more detail about each of these features by checking out the original post. Those who are unaware of how dataflows work in conjunction with Power BI to unify data and prepare it for modeling can learn more about it here.