Microsoft and the ubiquity of data intelligence

Microsoft and the ubiquity of data intelligence

Microsoft and the ubiquity of data intelligence
Microsoft’s had a very busy couple of months. On September 29th, it announced, and I wrote about, several enhancements to HDInsight, its cloud-based Hadoop and Spark Big Data offering. Then, one day later, the company released the September update to Power BI.

Also read: Microsoft HDInsight gets Spark 2.0, faster Hive, and better security Also read: Microsoft Power BI: A report card

Conference seasonAlong with the product releases, I had the opportunity last week to sit down and talk with Microsoft Corporate Vice President, Data Platform, Joseph Sirosh and his colleague Rimma Nehme, Technical Advisor, Data Platform. The conversation took place at in New York Strata + Hadoop World, where Sirosh had just keynoted, and did so right on top of another keynote at Microsoft’s own Machine Learning & Data Science Summit event, also held last week, in Atlanta.

As if that were not enough fodder for a post, I’ve just returned from developer conference Visual Studio Live! in Washington, DC, where I co-presented a workshop on SQL Server on Monday and delivered a solo session on HDInsight and another on Power BI, on Thursday.

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The conversation with Sirosh and Nehme provided me with Microsoft’s take on all of its efforts. My talks at Visual Studio Live! gave me the opportunity to assess developer reaction to Microsoft’s latest data and analytics updates, and to get very hands-on with both product updates so I could present them, properly. Put that all together, add in a day’s pondering, and there are some good findings to share.

Powering throughFirst, consider that many of the changes in Power BI involve integration of that product with others. For example, one big update involves the preview availability of ESRI ArcGIS for Power BI. This product provides for the extended mapping technology that ESRI is known for as well as the ability to layer in a vast array of demographic data for the United States and assorted other data from around the world, including for the Nepal earthquake and New Zealand predator control.

Another change is an enhancement to the already present integration of the R programming language: now, instead of having to create and edit your R code inside Power BI and its rather spartan code editor, you can shell out to any R IDE (integrated development environment) and Power BI will copy both your code and your data there so you can work productively in a richer environment, before copy and pasting your edited code back into Power BI.

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Further integration features included in the September update include new and enhanced connectors to various external data sources (all of them from other vendors, including Oracle and SAP); the ability to configure HTTP headers sent by Power BI’s Web connector, which can be used to connect to RESTful Web service APIs from other services and vendors; and the addition of a new mobile view for reports and dashboards, a feature almost identical to the that of the Datazen product Microsoft acquired in April, 2015, and which is currently integrated into SQL Server Reporting Services.

R-n’t we smart? Speaking of integrations, Microsoft has also integrated the R programming language into SQL Server 2016, and has done so in a way that lets SQL Server act as a production deployment server for visualization-producing stored procedures and even for R predictive models. In fact, Sirosh mentioned to me that, with SQL Server R Services, Microsoft has been able to get SQL Server to support the generation of 100 millionpredictions per second.

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Sirosh also mentioned that the company’s Azure Data Lake Analytics service, which features a SQL-like language (called U-SQL) for querying big data, which is extensible through .NET code written in C# or non-.NET code written in R or Python.

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