Microsoft on the Ascent in Business Intelligence and Data Science

Microsoft has been on a tear for the past couple of years. It has been pushing forward with a very steady stream of powerful new features and capabilities, even entire product lines, within its Data Platform business. But while Microsoft has been hard at work on this deluge of new technologies, it would be completely forgivable if you haven’t noticed. The reason it’s OK is that Microsoft is advancing on multiple fronts, both in the on-premises product line and even more dramatically with the Azure cloud-based products. In my experience, many IT shops only care about one or the other and thus fail to see the big picture of all the innovation. So let’s get caught up on what’s new when it comes to the online analytical processing (OLAP), business intelligence (BI), and data science side of the Microsoft Data Platform.

BI Means Self-Service

It’s no secret that the most effective organizations today have gradually shifted portions of their business intelligence efforts out of centralized IT departments and into their business units. This evolution is urgently driven by business needs for agility and autonomy. Business analysts can no longer afford the time to send a report definition off to IT and wait for the creation of a SQL report. At the same time, centralized IT cannot afford to let business analysts tinker around in their day-to-day online transaction processing (OLTP) database systems nor their important systems-of-record.

Microsoft has pushed hard to break down these contrasting barriers by introducing some of the most exciting features in BI today—Power BI and the new Power BI Desktop. I won’t go into a lot of additional detail about Power BI, since I wrote quite a lot about it back in August 2014 ( In summary, Power BI offers a complete set of data discovery, preparation, interactive drill-down, and data visualization capabilities that is most needed for agility and autonomy. Suffice it to say that the Power BI is an extremely strong contender in self-service BI. Plus, it is very inexpensive, priced at $9.95/month per user before any sort of licensing discounts.

Data Science Is Knocking and It Wants You to Come Out and Play

Data science, the art of applying statistical algorithms to extract real knowledge from data, has also come of age on the Microsoft Data Platform with the introduction of several new products within the Cortana Analytics Suite. The suite includes Power BI, Azure Machine Learning, Microsoft R Server, Business Scenarios, and the Cortana Personal Digital Assistant (Microsoft’s natural language processor). The suite is complemented by other services such as Azure Stream Analytics, Azure HDInsight (Microsoft’s implementation of Hadoop), Azure Data Factory, and SQL Server Analysis Services (and Azure SQL Data Warehouse in the cloud).

To get an overview of everything going on in the data science side of the house, I suggest starting either with Microsoft’s overview landing page or with its video series:

• For reading, start at

• For video, start at

And, if you’re looking for a good blog on the topic, I suggest you start with my buddy Buck Woody’s blog at His conversational tone and great examples make this material a much easier read.

A Competitive Differentiator

This is important stuff. Organizations that get on board with data science and decentralized BI now will outcompete by wide margins in the coming years their peers who do not. If you’ve only been thinking about your data in terms of your RDBMSs, then it’s time to catch up on everything going on in the world of data science. Personally, I believe that we as an industry are on the cusp of a new era. In a few years, our data platforms will be as different, structurally and perceptually, as client-server database applications were from the old mainframe and minicomputer applications. Start learning today!

Kevin Kline, a longtime Microsoft SQL Server MVP, is a founder and former president of PASS and the author of SQL in a Nutshell. Kline tweets at @kekline and blogs at