Microsoft has published a deep learning project under an open source license, MapR is expanding its free Hadoop and Spark training programs, and Gartner has fresh numbers to share about the advanced analytics market. Plus, a new study identifies a big obstacle to effective decision making. We've got all that and more in this week's big data roundup.
Let's start with Microsoft. This week, the company began offering a deep learning framework to support artificial intelligence applications, jumping on the same bandwagon as Google, Facebook, and Yahoo. Called the Computational Network Toolkit, Microsoft released the project on GitHub.
If this sounds familiar to you, it's because there are several other big companies that have contributed machine learning and advanced intelligence development efforts to open source in the last year.
[ Google is a big user of machine learning. Want to know more about its latest project? Read Google Taps Machine Learning To Make Smartphones Smarter. ]
Free Hadoop And Spark Training
Data science and big data are hot job skills these days, with more demand for these roles than there are qualified individuals to fill them. That's why a recent Glass Door report called data scientist the top job for work/life balance. With that in mind, there are plenty of people looking to gain skills in this area. And MapR, one of the big three Apache Hadoop distribution companies, is making things a little bit easier.
The company announced this week a plan to expand its free on-demand Hadoop and Spark training offerings.
So far more than 50,000 developers, analysts, and administrators have enrolled in the free MapR on-demand training program, the company said. The program offers training for developers, administrators, and data analysts, and offers certifications in the skills that it teaches. Coursework includes hands-on exercises, labs, and quizzes. Students can complete certification exams that lead to Hadoop and HBase professional designations.
This week, we also caught up with Informatica's new CEO Anil Chakravarthy, who provided us with an inside view of his company's philosophy on big data and how he planned to implement it this year and beyond. Chakravarthy said his new team is focused on helping customers extract the business value out of their big data investments.
Advanced Analytics Growing Fast
Market research firm Gartner this week said that advanced analytics continues to be the fastest-growing segment in the business intelligence and analytics market. It's forecasting 2026 revnues of $1.5 billion for the segment, an increase of almost 14% over 2015.
More importantly, by 2018 more than half of large organizations globally will compete using advanced analytics and proprietary algorithms, and that will cause the disruption of entire industries, according to Gartner.
"Advanced analytics has already been changing entire industries for over a decade and is a key factor for how most new entrants disrupt established markets and beat their incumbents — whether selling books, renting movies, borrowing money or even building a professional sports team," said Jim Hare, research director at Gartner, in a prepared statement. "Today, with fewer regulated monopolies and the Internet eliminating geographical boundaries, more companies are starting to use statistical analysis, predictive modeling, and decision optimization to compete, instead of using traditional approaches."
Also this week, EntepriseDB, a Postgres database company, announced version 9.5 of its EDB Postgres Advanced Server, which the company said increases performance and scalability.
And VoltDB announced version 6.0 of its software, adding geospacial query support for applications that rely on location for social and commercial interaction, such as real-time ridesharing and management of IoT sensor data.
Top Decision Makers And Collaboration
Finally this week, do you find that when decisions go to the very top group of executives that they might get stuck there? You aren't alone. A new study shows that powerful people are terrible at collaborating on decision making. They can be less creative and effective than a lower-level team. Leaders offer fewer creative solutions in a group and perform better when they are working alone. And do you know what makes it even worse? They have more trouble making decisions if they have too much data.
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