Our benchmark research into business technology innovation shows that analytics ranks first or second as a business technology innovation priority in 59 percent of organizations. Businesses are moving budgets and responsibilities for analytics closer to the sales operations, often in the form of so-called shadow IT organizations that report into decentralized and autonomous business units rather than a central IT organization. New technologies such as in-memory systems (50%), Hadoop (42%) and data warehouse appliances (33%) are top back-end technologies being used to acquire a new generation of analytic capabilities. They are enabling new possibilities including self-service analytics, mobile access, more collaborative interaction and real-time analytics. In 2014, Ventana Research helped lead the discussion around topics such as information optimization, data preparation, big data analytics and mobile business intelligence. In 2015, we will continue to cover these topics while adding new areas of innovation as they emerge.
Three key topics lead our 2015 business analytics research agenda. The first focuses on cloud-based analytics. In our benchmark research on information optimization, nearly all (97%) organizations said it is important or very important to simplify information access for both their business and their customers. Part of the challenge in optimizing an organization’s use of information is to integrate and analyze data that originates in the cloud or has been moved there. This issue has important implications for information presentation, where analytics are executed and whether business intelligence will continue to move to the cloud in more than a piecemeal fashion. We are currently exploring these topics in our new benchmark research called analytics and data in the cloud Coupled with the issue of cloud use is the proliferation of embedded analytics and the imperative for organizations to provide scalable analytics within the workflow of applications. A key question we’ll try to answer this year is whether companies that have focused primarily on operational cloud applications at the expense of developing their analytics portfolio or those that have focused more on analytics will gain a competitive advantage.
The second research agenda item is advanced analytics. It may be useful to divide this category into machine learning and predictive analytics, which I have discussed and covered in our benchmark research on big data analytics. Predictive analytics has long been available in some sectors of the business world, and two-thirds (68%) of organizations as found in our research that use it said it provides a competitive advantage. Programming languages such as R, the use of Predictive Model Markup Language (PMML), inclusion of social media data in prediction, massive scale simulation, and right-time integration of scoring at the point of decision-making are all important advances in this area. Machine learning also been around for a long time, but it wasn’t until the instrumentation of big data sources and advances in technology that it made sense to use in more than academic environments. At the same time as the technology landscape is evolving, it is getting more fragmented and complex; in order to simplify it, software designers will need innovative uses of machine learning to mask the underlying complexity through layers of abstraction. A technology such as Spark out of Amp-Lab at Berkeley is still immature, but it promises to enable increasing uses of machine learning on big data. Areas such as sourcing data and preparing data for analysis must be simplified so analysts are not overwhelmed by big data.
Our third area of focus is the user experience in business intelligence tools. Simplification and optimization of information in a context-sensitive manner are paramount. An intuitive user experience can advance the people and process dimensions of business, which have lagged technology innovation according to our research in multiple areas. New approaches coming from business end-users, especially in the tech-savvy millennial generation, are pushing the envelope here. In particular, mobility and collaboration are enabling new user experiences in both business organizations and society at large. Adding to it is data collected in more forms, such as location analytics (which we have done research on), individual and societal relationships, information and popular brands. How business intelligence tools incorporate such information and make it easy to prepare, design and consume for different organizational personas is not just an agenda focus but also one focus of our 2015 Analytics and Business Intelligence Value Index to be published in the first quarter of the year.
This shapes up as an exciting year. I welcome any feedback you have on this research agenda and look forward to providing research, collaborating and educating with you in 2015.