Building systems of insights at enterprise scale with Power BI and Azure | Microsoft Power BI Blog

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Today, Microsoft announced the general availability of Azure Synapse Analytics and the preview of Azure Purview, a unified data governance service. Azure Synapse Analytics is a limitless analytics service that brings together data integration, enterprise data warehousing, and big data analytics.

Azure Synapse Analytics and Power BI provide you with the capabilities to analyze massive volumes of data, efficiently and quickly, decreasing your time to insights. You can consume your existing Power BI datasets and reports or create new ones, based on your existing data – all this by just linking your Synapse and Power BI workspaces. Rockwell Automation has leveraged the Azure Synapse – Power BI integration and realized the benefits from this combination.

“We look at Azure Synapse Analytics and Power BI as the foundation of analytics that drive innovation, exploration and rapid development in the modern world.”

Chris Wagner: Enterprise Architect

In this blog, we will further discuss how you can enhance your enterprise analytics by adopting Azure Synapse and Power BI.

 

Performance

One of the key factors determining the time to insights is the performance of the underlying analytical solution. With growing data, there is a need for highly performant solutions to achieve and maintain response times. The tight integration between Azure Synapse and Power BI offers the capabilities needed to realize the desired time to insights. For example, you can leverage composite models and aggregations to benefit from both the scale of Azure Synapse and the performance of the Power BI Vertipaq engine. These features can be used to enable interactive analysis over petabyte-scale datasets.

Looking forward, we are continuing to invest in further performance optimizations. For example, we recently announced the private preview of the Power BI performance accelerator for Azure Synapse Analytics (Signup here). The process of creating materialized views (MVs), to tune the performance of a data warehouse, can be time and resource- consuming. Power BI’s machine learning (ML) based algorithm automatically determines MVs to create and recommends those to Azure Synapse, which in turn creates the recommended views. Power BI queries can then use materialized views, instead of the underlying tables, to significantly boost performance. This process is self-learning and optimizes itself over time, saving time and resources.

 

Integrated Monitoring

The ability to monitor and troubleshoot your resources is critical to maintain reliability in your analytical platform. Customers can bring their own Azure Monitor (an Azure based diagnostic service) and have their Power BI telemetry sent to Azure Log Analytics (a sub-service within Azure Monitor). Having the telemetry, which will be correlated, in a single store, offers the opportunity to obtain an end-to-end view of your analytical processes, from your reports to your DAX queries to your SQL queries. You can examine engine query information to identify trends or easily identify specific problem areas within time ranges, workspaces, reports, or queries. You will also be able to see the relationships and timings between DAX queries and external SQL queries, including the utilization of MVs generated by the Intelligent Performance Accelerator. Furthermore, you can view and leverage these metrics instantly, by installing a template application, to gain deeper insights. This feature will be available for preview in the first quarter of 2021.

 

Data Governance 

Governance of data is critical and to make critical business decisions, discovering the right, high-quality data assets you can trust, and reuse is imperative. Power BI has partnered with Azure Purview to make it simple to discover, understand and govern your data assets. Leveraging this partnership, your Power BI assets metadata and connections can now be scanned into the Purview data catalog. Once scanned, key features are enabled for users including effective data governance, deriving end-to-end data lineage across your entire data stack, data source impact analysis for troubleshooting or upon planned changes, defining a business glossary, and ensuring data protection leveraging visibility of Microsoft Information Protection (MIP) sensitivity labels on the various assets. You can now preview this feature (during the preview, enable scanning Power BI tenants for free)

 

 

Next Steps

Join us today at the ‘Shape Your Future with Azure Data and Analytics’ digital event with Satya Nadella.

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