Self-Service Analytics with Microsoft Power Platform

The Power Platform Self-Service Analytics empowers users to use the Data Export function from the Power Platform admin centre. This allows for the information regarding Power Apps and Power Automate Flows to be transported to an Azure Data Lake. The data is exported daily, paving the way for comprehensive analytics.

The data can be analyzed using various platforms such as Power BI, Azure Data Factory and Synapse Analytics. Utilizing Azure Subscription and Azure Data Lake will help set up Data Export. A Hierarchical Namespace-enabled Blob Storage Account is required for creating Azure Data Lake.

To continue, the Power Platform Admin Center is accessed and the Data Export option is selected. The user then decides which information to be exported (Power Automate or Power Apps) and provides necessary details regarding the storage account. It's noteworthy that filtering options are currently unavailable which means all the Power Apps and Flows inventory and data usage within a user's tenancy will be included. Typically, it takes a day to two before the export starts pushing data to your Data Lake.

Finding Your Data and Analyzing It

Once the Data Export process commences, a container known as 'powerplatform' gets created with folders labeled as 'powerapps' and 'powerautomate'. One particular folder of interest is the 'powerplatform/powerautomate/usage' folder. Here, users will find a file for each day, shedding light on all Power Automate runs executed on that specific day. The caveat here is that the most recent usage data trails two days behind, however, this might improve as the Data Export feature becomes officially available.

The Data Export service mirrors the functions of Synapse Link for Dataverse that we have discussed in earlier articles. Yet, the analytics data is presented in JSON format rather than raw data like Synapse Link. JSON or semi-structured data must be parsed before it can be used, and details on the schema can be found within the Flow usage files.

Users can utilize different ways to analyze the data in their Data Lake, one of them being the Power BI tool. They may need to select Azure Data Lake Storage Gen2 as their source to query data from this business analytics service tool. The user can then enter the URL where the data resides. Ensuring that the dfs structure has been used in the URL guarantees that no errors will be experienced.

After you authenticate your connection, you can then combine and transform the data. This will provide full access to your Power Automate flow usage data in this analytics service. The provided information is intuitive with each property or column holding distinct data. For instance, the 'resourceId' is equivalent to the 'workflow guid' and the 'status' column reveals whether the flow run was successful or unsuccessful.

While the Power Platform analytics is still in the review stage, its ability to automatically export your data to a Data Lake looks promising. Once the data is in your data Lake, a wide array of tools like Power BI, Azure Data Factory, and Synapse Analytics can be used to analyze and surface the data. There's room for adaptability when it comes to analyzing this data. For instance, users can query this data directly from the Data Lake, or leverage Azure Data Factory to move it into a database or Dataverse.

Users could also consider using the Power Platform Data Export option instead of the Microsoft Power Platform Center of Excellence for monitoring their inventory and usage. The expansive capabilities of this service give vast opportunities for overviews and detailed reporting, making it a viable consideration for those who rely on analytics.

Read the full article Power Platform Self-Service Analytics

Learn about Power Platform Self-Service Analytics

The ability to efficiently manage and analyze data is a highly sought skill in our modern digitally driven society. Self-service analytics has emerged as one of the most effective ways of dealing with vast amounts of data. You can develop your abilities in this area by familiarizing yourself with Microsoft Power Platform Admin Center's analytic tools such as the Data Export option, Power Apps, and Power Automate Flows, among others.

• Introduction to Power Platform Admin Center Data Tools

This platform provides a versatile set of tools specifically designed for easy data management and analysis. The Data Export option, in particular, allows you to export detailed information and usage data from your Power Apps as well as Power Automate Flows to an Azure Data Lake. This allows for easy and efficient self-service analytics.

• Setting Up Data Export

Configuring Data Export is a straightforward process. For starters, you need an Azure subscription coupled with a pre-created Azure Data Lake. It's worth noting that the Azure Data Lake is constructed on top of Gen2 Blob Storage. As such, creating a Blob Storage Account with a Hierarchical Namespace enabled is all that is required.

• Use of Other System Tools

Moreover, from the Data Lake, you can leverage the use of a myriad of tools for self-service analytics. Several remarkable examples include Azure Data Factory, Synapse Analytics, and the self-service BI to unlock deeper insights into your data.

• Exploration of the Powerplatform

In exploring the system data structure, you'll come across a 'powerplatform' container. This has been further split into 'powerapps' and 'powerautomate'. Included in the 'powerautomate' section is a usage folder that contains a file for each day of Power Automate runs. The structure gives a simplified and clear data organization for users.

• Reading the Data

To effectively read and analyze the data exported, the system provides it in JSON format, a semi-structured data format. This user-friendly structure makes it easier to interpret the data. In Power Automate usage files, each line contains a JSON object that gives specific details of a flow run.

• Linking Power Platform with the Self-service BI

How, you might ask, can you read this data in the self-service BI? After pointing the source to Azure Data Lake Storage Gen 2, you are required to authenticate your connection. The data is then combined and transformed to give you clear access to Power Automate flow usage data.

• Final Remarks

In summary, the power to automatically export your Power Platform analytics to Azure Data Lake is an impressive capability still under preview. Apart from using the self-service BI, this feature presents the option of using the Power Platform Data Export for monitoring your Power Platform inventory. It indeed seems like an incomparable self-service analytics tool.

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