Microsoft aims to do one thing better than anyone else: bring the power of productivity tools, big data, machine learning and data driven insight to both every day Jacks and Jills and geeks, and makes it look simple. How does it propose to do that? There’s Bing that tells Cortana who will win the World Cup and the Super Bowl, Delve that surfaces the content that’s most relevant to you without your needing to ask, Power BI that puts data driven insights and impressive, informative viz’s at your fingertips, Hadoop and machine learning delivered in the cloud, on premises and even on a silver platter (OK, maybe we’re going a bit too far).
The Name of the Game is Simple
But instead we’ll bring you up to date on the news that Microsoft is making at the Strata and Hadoop World conference being held in San Jose, Calif. this week because it’s shiny, new and holds the potential to yield nearly immediate results for your business as well as those who don’t even use Windows. The bottom line?
“Microsoft wants to make it easy and simple to work with data,” explained T. K. “Ranga” Rengarajan, corporate vice president, Data Platform, during an interview yesterday. His team intends to do so by leveraging Microsoft’s assets as well as those that can be found in open source and/or are provided by partners.
The solutions are geared toward varied audiences ranging from big data pros, data scientists and app developers, to everyday businesspeople and IT managers. They leverage data drawn from the Internet of Things (IoT), data warehouses and operational intelligence, among other sources.
Today’s news revolves around new and enhanced data services on Azure, Microsoft’s cloud.
First up is the availability of Azure HDInsight, Microsoft’s Apache Hadoop-based service in the cloud. It can now run on Linux (more specifically Ubuntu clusters). This opens up possibilities for companies that already run Linux on premises, which some Hortonworks customers do, because they can use the same set of tools, templates and documentation to create hybrid scenarios.
Second, Storm for Azure HDInsight which we wrote about last fall when it was in preview is now generally available. Apache Storm, you might remember, is an open source stream analytics platform that can process millions of events (such as those generated by IoT) in real time. It’s worth noting that ad services provider, Linkury, leverages the technology to track 150 million events each day and has only one developer on staff. Talk about democratizing big data.
Third is Azure Machine Learning a managed cloud service for advanced analytics that uncovers new ways to leverage data to predict the future. A practical example of this might be gathering and analyzing elevator data to look for unusual patterns or outliers. Why do this? Because it may hint of an impending elevator breakdown which is better prevented than surfaced when you’re stuck between floors in a skyscraper.
One of the big wins from this solution is its quick time to value. Rengarajan says that within a few hours data scientists and developers can build and deploy apps to improve customer experiences, predict and prevent system failures, enhance operational efficiencies, uncover new technical insights, or a universe of other benefits. Without such a solution it can take weeks, or even months, to get the job done, never mind the investment in people, hardware and software to manage big data.
Also, now developers -- even those without data science training -- can use Microsoft’s Machine Learning Marketplace to find APIs and finished services, such as recommendations, anomaly detection and forecasting, in order to deploy solutions quickly.
Microsoft also has a machine learning announcement for data scientists and those who want to code, says Rengarajan. The Python programming language is now a first class citizen in Azure Machine Learning Studio, along with R, the popular language of statisticians.
You've Come a Long Way
At the end of the day, we have Microsoft which is quickly becoming a favorite of geeks and non-geeks alike. It’s a far cry from where it was a few years ago when it looked more like a has been than an innovator.