Power BI Streaming Dataflows October Update
We are thrilled to announce some exciting new capabilities for streaming dataflows in Power BI
As a reminder, streaming dataflows allow authors to connect to, ingest, mashup, model, and build reports but based on continuous streaming, near real-time data. This is done directly in the Power BI service with beautiful, drag and drop, no-code experiences.
In this month update we are announcing two new capabilities
Streaming support for Azure blobs
As of today, streaming dataflows support two inputs: Azure Event Hubs and Azure IoT Hubs. With this new release, we are announcing a third option: Azure blobs. You can now connect and ingest data from a container or directory using file name patterns to bring data into streaming dataflows. This unlocks many new scenarios including analyzing log analytics data that is backed by Azure blobs.
Using static data with streaming dataflows
Often, when working with real time data, data will be condensed, and Identifiers are used to represent the object. In this new release, we are pleased to announce support for reference data. Reference data allows you to join static data to streaming data to be used for analysis. Lets go through a quick example of when this would be helpful. Imagine you install sensors at different departments stores to measure how many people are entering the store at a given time. Usually, the sensor ID needs to be joined onto a static table to indicate which department store and which location the sensor is located at. Now with reference data, it is possible to join this data during the ingestion phase to make it easy to see which store has the highest output of users.
Start your streaming dataflow journey today
To start your streaming dataflow head to the workspace and hover over your streaming dataflow’s name. You will see a “play” icon. Click it and your dataflow will start. To learn more, click here.
