What’s (v)Next on SQL Server for Business Intelligence and Analytics

On April 19, Microsoft announced the new name for the next version of SQL Server–SQL Server 2017–along with the second CTP (Community Technical Preview 2.0).  Last year, the release of SQL Server 2016 delivered significant improvements and added functionality to Microsoft’s on-premises BI capabilities, most notably with many substantial updates to Reporting Services and integration with the R programming language.

Now, just a year later, Microsoft is getting ready to release a new wave of enhancements with SQL Server 2017.  Below I highlight some of the most exciting new features coming with this new release, with an eye towards how these features can be leveraged to enhance your BI and Analytics capabilities.

Reporting Services

One of the most anticipated updates for Reporting Services in the 2017 release is integration with Power BI desktop reports.  You will finally be able to host and view Power BI desktop reports within the reporting services website. Now, even those that are cloud-adverse can develop and deploy Power BI desktop files to everyone in their organization.

An important note to include is that as of today, this only works in conjunction with Analysis Services Tabular Models (with plans to add additional connectors by the 2017 GA release). There is a ton of great information on all aspects of this and other updates to Reporting Services on the SQL Server Reporting Services Team Blog.

Analysis Services

All improvements to SSAS (SQL Server Analysis Services) made in 2017 are focused on the Tabular Model, showing Microsoft’s commitment to developing this tool.  Here are a few of the highlights:

  • Object-level security – As of CTP 2.0, you will now be able to dynamically hide/show certain columns and entire tables to specific users. Prior to 2017, you were only able to filter on the row level.
  • New “Get Data” experience for in-memory models – The data import process now resembles that of Power BI desktop, along with the large number of connectors that currently exist in Power BI. You can read more about this component here.
  • Processing and transaction – performance improvements

A complete list of all the new features can be found here.

Advanced Analytics

Along with various features aimed at improving upon the R Server integration released with SQL Server 2016, including an improved processing and developer experience, Microsoft is renaming its SQL Server R Services “Machine Learning Services (In-Database).”

This name change came with an exciting and unexpected update. In the SQL Server 2017 CTP 2.0, Microsoft announced integration with the Python language. This means that you will be able to leverage the two most popular programing languages used by data scientists (R and Python) to create and deploy machine-learning algorithms.

This surprising update has garnered a lot of attention and warrants an entire series of posts devoted to it.  Keep an eye out for future blog posts from us on this topic. Until then, you can read more about the implications and details of this feature from one of my favorite blog posts on the topic here.

Want to learn more about this and the other features being introduced with the 2017 release? Email info@peters.com or call 630.832.0075. We are happy to help!

By | 2018-12-18T11:07:11+00:00 April 28th, 2017|Business Intelligence, Collaboration|Comments Off on What’s (v)Next on SQL Server for Business Intelligence and Analytics

About the Author:

Andrew Failor is a Data Analytics Consultant at Peters and Associate. Andrew is responsible for exposing and extracting critical data, automating analysis to optimize business processes and digging deep in to data to maximize impact on the businesses of our clients and focuses on communicating the quickly changing and evolving data analytics space and extracting relevance for our client’s businesses. He has experience across a large variety of analytics and business intelligence solutions, including software products, industries and lines-of-businesses. Andrew holds a Bachelors of Business Administration in Business Analytics and Information Systems and Analytical Economics.