We dive into some of the benefits of Microsoft Synapse, sharing three reasons to consider using the tool for your next data and analytics project.
A recent project had me working with Microsoft Synapse, and I must say, I am impressed. I have heard more than once that Synapse is only a re-branding exercise of existing Microsoft services. The marketing team at Microsoft hasn’t helped the situation by describing Synapse as “Azure SQL Data Warehouse evolved.”
In reality, Synapse is so much more than that – it is Microsoft’s new unified cloud analytics platform. Here are a few reasons you should take a serious look at using Synapse for your next data analytics project.
Together as One, and Then Some
Historically, Azure has offered a myriad of data services. Individually leveraged, these services are compelling, but finding the right mix of services and integrating them has always been challenging. Azure Synapse solves this problem by bringing together the best of Azure’s existing data services, adding some powerful new features, and then makes them all play together very nicely.
Your favorite services like Azure Data Factory, Mapping Data Flows, Power BI and of course SQL Pools (formally SQL Data Warehouse) come together in a unified data platform, and that is a big deal.
From an intuitive web-based UI, you can now explore data, run “experiments,” develop pipelines and operationalize solutions. If you are a long-time Microsoft user, Synapse makes it appear like Microsoft finally designed all of these disparate services to work together. As the product matures, my hope is this tool will continue to look more and more seamless.
Synapse offers its own managed Spark environment. Microsoft based this environment on Apache Spark 2.4 with Python 3.6. Gone are the days (and sometimes nights) of laboring through configurations before being productive. You can integrate sign-on and security. The process of connecting to storage accounts is very straightforward. If you have been frustrated with Cluster start-up times, Synapse is “peppy,” and that is a nice change of pace if you are running spark jobs as part of your data pipelines.
Synapse also comes with .NET bindings for Spark. This means you can now take advantage of Spark without needing to learn a new language. The notebook experience allows you to write all your analytics queries in .NET or even to mix match with more traditional options such as PySpark, Scala or Spark SQL. This is really helpful for entities who have existing .NET teams and legacy skills.
I started this post talking about Synapse being “together as one, and then some.” Part of the “then some” I am talking about is the Power BI integration. Power BI workspaces integrate directly with Synapse. You can access reports and datasets within Synapse studio, and you can create new datasets and reports with ease from the data you curated in Azure Synapse.
Since SQL Serverless looks like any regular SQL database, you can easily run powerful analytical queries during import, and you still retain all the usual data connectors you are accustomed to using. For the 13th consecutive year, Microsoft has been positioned as a leader in the Gartner 2020 Magic Quadrant for Analytics and Business Intelligence Platforms.
It is prudent to note that Microsoft is positioned furthest to the right for two straight years for completeness of vision and furthest up in executing within the leaders’ quadrant. Historically, Power BI has focused on business users. Synapse now puts Power BI firmly in the hands of data professionals — a welcome move that is already yielding results for our clients.
Is your organization looking for ways to leverage data but has struggled to extract the value from the data available to them? This inability to turn data into useful insights is not all that surprising, given a modern data landscape that is far more complex than just a few years ago. The number and type of data sources have exploded, as has the volume of data they produce. Using a tool like Microsoft Synapse can significantly improve your ability to navigate this data.