Business Analytics in 2014: Trends and Possibilities
Our benchmark research shows that analytics is the top business technology innovation priority; 39% of organizations rank it first. This is no surprise as new information sources and new technologies in data processing, storage, networking, databases and analytic software are combining to offer capabilities for using information never before possible.
Our benchmark research shows that analytics is the top business technology innovation priority; 39% of organizations rank it first. This is no surprise as new information sources and new technologies in data processing, storage, networking, databases and analytic software are combining to offer capabilities for using information never before possible. For businesses, the analytic priority is heightened by intense competition on several fronts; they need to know as much as possible about pricing, strategies, customers and competitors. Within the organization, the IT department and the lines of business continue to debate issues around the analytic skills gap, information simplification, information governance and the rise of time-to-value metrics. Given this backdrop, I expect 2014 to be an exciting year for studying analytic technologies and how they apply to business.
Three key focus areas comprise my 2014 analytics research agenda. The first includes a specific focus on business analytics and methods like discovery and exploratory. This area will be covered in depth in our new research on next-generation business analytics commencing in the first half of 2014. At Ventana Research, we break discovery analytics into visual discovery, data discovery, event discovery and information discovery. The definitions and uses of each type appear in Mark Smith’s analysis of the four discovery technologies. As part of this research, we will examine these exploratory tools and techniques in the context of the analytic skills gap and the new analytic process flows in organizations. The people and process aspects of the research will include how governance and controls are being implemented alongside these innovations. The exploratory analytics space includes business intelligence, which our research shows is still the primary method of deploying information and analytics in organizations. Two upcoming Value Indexes, Mobile Business Intelligence, due out in the first quarter, and Business Intelligence, starting in the second, will provide up-to-date and in-depth evaluations and ranking of vendors in these categories.
My second agenda area is big data and predictive analytics. The first research on this topic will be released in the first quarter of the year as benchmark research on big data analytics. This fresh and comprehensive research maps to my analysis of the four pillars of big data Analytics, a framework for thinking about big data and the associated analytic technologies. This research also has depth in the areas of predictive analytics and big data approaches in use today. In addition to that benchmark research, we will conduct a first of its kind, the Big Data Analytics Value Index, which will assess the major players applying analytics to big data. Real-time and right-time big data also is called operational intelligence, an area Ventana Research has pioneered over the years. Our Operational Intelligence Value Index, which will be released in the first quarter, evaluates vendors of software that helps companies do real-time analytics against large streams of data that builds on our benchmark research on the topic.
The third focus area is information simplification and cloud-based business analytics including business intelligence. In our benchmark research on information optimization, recently released, nearly all (97%) organizations said it is important or very important to simplify information access for both their business and their customers. Paradoxically, at the same time the technology landscape is getting more fragmented and complex; in order to simplify, software design will need innovative uses of analytic technology to mask the underlying complexity through layers of abstraction. In particular, users need the areas of sourcing data and preparing data for analysis to be simplified and made more flexible so they can devote less time to these tasks and more the actual analysis. Part of the challenge in information optimization and integration is to analyze data that originates in the cloud or has been moved there. This issue has important implications for debates around information presentation, the semantic web, where analytics are executed, and whether business intelligence will move to the cloud in any more than a piecemeal fashion. We’ll explore these topics in benchmark research on business intelligence and analytics in the cloud, which is planned for the second half of 2014. We released in 2013 research on location analytics and the use of geography for presentation and processing of data which we refer to as location analytics.
Analytics as a business discipline is getting hotter as we move forward in the 21st century, and I am thrilled to be part of the analytics community. I welcome any feedback you have on my research agenda and look forward to continuing to providing research, collaborating and educating with you in 2014.
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