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Charting the Expanding Horizons of Big Data: Report IDs Key Trends Surrounding Adoption, Expectations and Challenges

9sight Consulting, Associates, Big data, data and information practice, Data management, data research, Dr. Barry Devlin, EMA, enterprise management, John L. Myers, Lyndsay Wise, Marketing, non-traditional data, Pr, Public relationsBig data offers a wide range of possibilities—but the term “big data” still keeps media and industry eyes focused on size as the defining feature, to the detriment of other important and evolving aspects of data and information practice, according to new research from IT and data management research and consulting firm Enterprise Management Associates (EMA) and strategic consulting firm 9sight Consulting, which recently released their annual big data research report, Charting the Expanding Horizons of Big Data: Big Data 2016. The research explores the wide range of ways in which non-traditional data, often in combination with more traditional types, enables new or improved business processes.

Based on research criteria defined by John L. Myers, managing research director of EMA, Lyndsay Wise, research director of EMA, and Dr. Barry Devlin, founder and principal of 9sight Consulting, this new report leverages feedback from 303 business and technology stakeholders worldwide.

“Big data initiatives around the globe continue to develop and mature. Organizations with robust strategies are making the most of their environments, while those organizations with less established strategies continue to refine and develop their implementations,” said Myers, in a news release. “The core components of EMA’s Hybrid Data Ecosystem, a blueprint for next-generation data management environments, continues to provide a framework for big data technical architectures.”

Speed and the concept of streaming data, or data in motion, have grown in importance for respondents. Within the scope of their projects, EMA respondents continue to include a wide range of data structures, from highly structured information from platforms such as operational systems and the enterprise data warehouse, to variable data structures associated with sensor and machine-generated data (such as log information and sensor data). The 2016 survey also included investigations into the highly visible topics of data-driven culture, streaming platforms for integration and analytics and data lake architectures and implementations.

“Our data lake findings were particularly interesting. There was a large increase in implementation, with two thirds of respondents now having adopted a data lake approach,” said Devlin, in the release. “However, respondents differed greatly as to what that actually entailed in their data lake implementations, indicating extreme confusion about how data lakes relate to other data management concepts.”

Some of the key findings from this new report include:

  • Understanding the Customer is Job #1—Robust maturity scoring organizations are focused on customer engagement with their big data projects. The top two business goals relate directly to engaging with and analyzing customer information using advanced analytics.
  • Big Data! Big Time!—Nearly 9 of 10 respondents are adopting big data strategies in 2016. The growth of respondents adopting those strategies shows over 22% growth from the previous EMA/9sight study in 2014/2015.
  • Strength in Numbers—Over 60% of respondents indicated that their big data environments, such as the Hybrid Data Ecosystem, included between 2 and 5 different platforms.
  • Balance Comes with Experience—Organizations with Robust classification in the EMA Big Data Maturity scoring are better-rounded with their application of use cases. Organizations with Struggling or Ineffective scores tend to focus on Analytics and Exploration use cases.
  • Increasing Chances of Success—Over 7 of 10 big data projects have some form of success, with 41.3% of projects experiencing moderately successful results. This is a growth of over 20% from the results in the 2014/15 survey.

The report also introduces EMA’s Big Data Maturity Scoring Model, and explains how organizations of differing strategy, implementation and success attributes can compare themselves against one another as they continue their implementation journey associated with big data.

Get more information about the study here.

Access an on-demand webinar discussing the research here.

Source: PRWeb; edited by Richard Carufel

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