Ventana Research Analyst Perspectives

About the Analyst

David Menninger

David is responsible for the overall research direction of data, information and analytics technologies at Ventana Research covering major areas including Analytics, Big Data, Business Intelligence and Information Management along with the additional specific research categories including Information Applications, IT Performance Management, Location Intelligence, Operational Intelligence and IoT, and Data Science. David is also responsible for examining the role of cloud computing, collaboration and mobile technologies as they affect these areas. David brings to Ventana Research over twenty-five years of experience, through which he has marketed and brought to market some of the leading edge technologies for helping organizations analyze data to support a range of action-taking and decision-making processes. Prior to joining Ventana Research, David was the Head of Business Development & Strategy at Pivotal a division of EMC, VP of Marketing and Product Management at Vertica Systems, VP of Marketing and Product Management at Oracle, Applix, InforSense and IRI Software. David earned his MS in Business from Bentley University and a BS in Economics from University of Pennsylvania.

Recent Posts

At Strata Data NY, Focus is on Machine Learning and AI

Posted by David Menninger on Nov 19, 2017 7:30:13 AM

The Strata Data Conference is changing and it’s changing in a good way. At the recent Strata Data Conference in New York, Mike Olson, chief strategy officer at Cloudera, which co-sponsored the event, commented that at prior events we used to talk about the “Hadoop zoo animals,” meaning the various components of the Hadoop ecosystem of which I have written previously. Following last fall’s Strata event, I observed that the conference was evolving to focus on the use of data. Advancing that evolution, this year’s event focused on a particular type of usage: artificial intelligence (AI) and machine learning. The evolution from a focus on zoo animals to a focus on business value using advanced analytics shows further maturation of the big data market.

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Topics: Big Data, Machine Learning, Analytics, Hadoop, Artificial intelligence

Is Hadoop Disappearing?

Posted by David Menninger on Nov 9, 2017 7:45:05 AM

There’s been some speculation in the market that Hadoop may be disappearing. Some of this speculation has been driven by vendors that have recently downplayed Hadoop in their marketing efforts. For example, the Strata+Hadoop World conference is now known as the Strata Data Conference. The Hadoop Summit is now known as the Dataworks Summit. In Cloudera’s S-1 filing with the SEC for its initial public offering, the term “Hadoop” appears only 14 times, while the term “machine learning” appears 83 times. So, if some of the vendors that created the market appear to be pivoting away from Hadoop, does your organization need to do something similar, or is there a role for Hadoop in your IT architecture?

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Topics: Big Data, Analytics, Hadoop

Hortonworks Helps IBM Big Data Potential with Hadoop

Posted by David Menninger on Sep 4, 2017 9:35:27 AM

Recently Hortonworks announced some significant additions to its products at the DataWorks Summit. These additions reflect the fact that the big data market continues to evolve, as I have previously written.

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Topics: Big Data, Machine Learning, Analytics

Natural Language Generation Broadens the Reach of Analytics and BI

Posted by David Menninger on Sep 1, 2017 10:09:02 AM

Natural language generation (NLG), the process of generating text or narratives based on a set of data values, can reach a broader audience. NLG narratives can be used for a variety of purposes, but in this perspective I focus on how NLG can be used to enhance business intelligence (BI) processes. In the case of BI, NLG can be used to explain what has happened and why it is happening, and even what actions to take. The NLG narratives can be understood by a broader range of business users than the tables and charts of data that are the typical output of most BI applications or analytics tools.

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Topics: Machine Learning, Natural Language, Analytics, Business Intelligence

Datawatch Gets Social with Data Preparation

Posted by David Menninger on Aug 24, 2017 3:06:55 AM

Many organizations continue to struggle with preparing data for use in operational and analytical processes. We see these issues reported in our Data and Analytics in the Cloud benchmark research, where 55 percent of organizations identify data preparation as the most time-consuming task in their analytical processes.  Similarly, in our Next-Generation Predictive Analytics research, 62 percent of companies report that they’re unsatisfied because data needed for access or integration is not readily available. In our Big Data Integration research, 52 percent report spending that in working with big data integration processes, they spend the most time reviewing data for quality and consistency.  And nearly half of companies (48%) report this same issue in our Internet of Things research. We are currently conducting further research into this critical issue with our Data Preparation benchmark research.

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Topics: Analytics, Collaboration, Data Preparation, Datawatch