Virtualization Technology News and Information
Datameer 2017 Predictions: What's Big in Big Data for 2017

VMblog Predictions 2017

Virtualization and Cloud executives share their predictions for 2017.  Read them in this 9th annual series exclusive.

Contributed by Andrew Brust, Senior Director, Market Strategy/Intelligence and Joanna Schloss, Director of Product Marketing, Datameer

What's Big in Big Data for 2017

Andrew Brust

In 2017, the reports of Big Data's death will be greatly exaggerated, as will the hype around IoT and AI.  In reality, all of these disciplines focus on data capture, curation, analysis and modeling.  The importance of that suite of activities won't go away unless all businesses cease operation.

Joanna Schloss

1. Hadoop distribution vendors will have crossed the chasm - unstructured data in Hadoop is a reality.  But, since the open source problem has not been addressed, they aren't making much money.  As such, there will be an acquisition of many of these vendors by bigger players.  As well as the idea that bigger ISV Hadoop vendors will band together and create larger entities in hopes of capitalizing on the economy of scale.

2. Data preparation will become more of a feature rather than a market as big data analytics continue to evolve both in product offerings and market share. As such, there may be a consolidation in the marketplace as companies start to acquire product offerings in this area as well as customer lists from small, niche vendors.

3. Artificial intelligence, machine learning, and advanced analytics will become more complex as people start to realize the true potential of these disciplines. All three areas require an excellent understanding of big data and big data analytics and they can eventually evolve into a master discipline of Analytics - or maybe we coin new term for it in the near future.

4. By the end of 2017, the idea of deep learning will have matured and true use cases will emerge. For example, Google uses it to look at faces and then determine if the face is happy, sad, etc.  There are also existing use cases in which the police is using it to compare the "baseline" facial structure to "real time" facial expressions to determine intoxication, duress or other potentially adverse activities.  


About the Authors

Andrew Brust, Senior Director, Market Strategy and Intelligence

Andrew Brust has worked in the software industry for 25 years as a developer, consultant, entrepreneur and CTO, specializing in application development, databases and business intelligence technology. He has been a developer magazine columnist and conference speaker since the mid-90s, and a technology book writer and blogger since 2005. Andrew serves as Senior Director, Technical Product Marketing and Evangelism at Datameer, a big data analytics company.

Andrew Brust 

Joanna Schloss, Director of Product Marketing

Joanna Schloss is a subject matter expert in data and information management, and drives product marketing tactics and strategy as director of product marketing at Datameer. Her areas of expertise include big data analytics, business intelligence, business analytics and data warehousing. With a blend of experience in both startup and G500 environments, Joanna has successfully launched a myriad of products, from business-focused analytic applications to data warehousing tools such as Business Objects Data Services. 

Joanna Schloss 

Published Friday, November 18, 2016 7:00 AM by David Marshall
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