The fourth EMA / 9sight Big Data Survey was conducted in March 2016, with the results published in November.
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. As established in previous surveys, big data offers a wide range of possibilities, but the name “big data” itself still keeps media and industry eyes focused on size as the defining feature to the detriment of other important and evolving aspect of data and information practice.
Speed and the concept of streaming data, or data in motion, have grown in importance for respondents. Within the scope of their projects, 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.
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.