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GP Bullhound, the investment firm behind the research says prescriptive analytics will fuel the next big wave of enterprise tech m&as

GP Bullhound, the investment firm behind the research says prescriptive analytics will fuel the next big wave of enterprise tech m&as

Growing at a rate of 56 per cent annually and pegged to reach $7.4bn by 2017, big data is one of the fastest growing sectors in technology today. Big data analytics has garnered $1.4bn worth of investment over the past 12 months, over 200 per cent more than last year according to research published Friday. The investment banking firm that commissioned the research says the results suggest the industry is about to enter a new stage of consolidation dominated by enterprise IT incumbents.

The shift from performing long batch analyses on information stored in vast data warehouses towards performing real-time analyses of data in the cloud is starting to reach critical mass, according to GP Bullhound, a tech-focused investment banking firm.

The firm’s research suggests that, as enterprises come to grips with emerging infrastructure and big data storage technologies, there will be significant growth in the number of information workers using analytics over the next three years. The firm estimates that just 17 per cent of information workers currently use big data analytics in their jobs, but that this will rise to reach over a third of information workers by 2016, driven in part by the growing prevalence of data visualisation software.

“Data visualisation is not new; the concept of displaying data in insightful ways has been around for several generations of Business Intelligence software over the last four decades. However, several emerging visualisation solutions are taking usability and functionality to such new heights that we expect a dramatic uplift in the number of users of Analytics software globally,” the authors write.

An important element here is the improved integration and plug-and-play nature of these front-end data visualisation analytics applications. Vendors are getting better at building in support for a growing range of SQL and NoSQL databases that contain structured and, increasingly, unstructured data.

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This growth rate of unstructured data – which now outpaces growth in structured data three to one – is to an extent the catalyst for the adoption of distributed file system technologies like MapReduce and Hadoop, which are leading to a new revolution in business intelligence (BI). BI was previously limited by technologies (and the rigidity of schema) in terms of what could reasonably be asked in a traditional data warehouse setting.

“Big data analytics is forward looking and more concerned with answering the Why and How questions, and indeed revealing questions that were not previously considered relevant. Where BI deals in known unknowns, big data analytics is better placed to reveal unknown unknowns,” the authors say.

Enterprises often struggle with these kinds of implementations for reasons beyond cost and complexity. The quality of existing data reporting which can be quite poor in some cases can often set the trajectory for future data-driven projects.

Interestingly, the firm believes applications, as opposed to infrastructure software and database technology, will see the highest levels of growth over the next three years. That’s not to say back-end infrastructure technologies like Hadoop won’t increase over time. But their adoption is still hamstrung by their relative youth, which often forces businesses to seek (costly) services from a small group of experts.

Still, that’s beginning to change. “We are already starting to see increased ease of use come through with the latest iterations of Hadoop. For example, Hadoop 2.0, which has just been released, allows for other processing algorithms besides MapReduce, which has to date been the most challenging aspect of Hadoop to develop code for,” they said.

Nevertheless, the increased availability and accessibility of these technologies means they are no longer the preserve of PhD data scientists. That said, the firm claims predictive analytics will be the next big wave in big data, particularly as companies innovating in the space gain more experience deploying, testing and tweaking their algorithms, and get better at combining them with machine learning technologies.

Big data acquisitions“In our view, the key innovation for predictive analytics over the next few years will be democratising existing algorithms for business users in real-time, rather than creating ever more complicated mathematics,” the authors said, adding that predictive analytics will likely fuel the next big wave of industry consolidation that will largely see the continued dominance of entrenched vendors.

“This last wave saw a small number of BI leaders – e.g. Business Objects, Cognos, Hyperion – gain scale in the early 2000s via a series of acquisitions, before, in 2007, the three incumbent Enterprise Software market leaders registered the strategic importance of BI, and all announced mega transactions: Oracle-Hyperion (March, $3.3bn), SAP-Business Objects (October, $6.8bn), IBM-Cognos (November, $4.9bn). Another recent round of competitive m&a between these three giants was for cloud-based HCM software (2011/12), in which SAP bought SuccessFactors, Oracle bought Taleo, and IBM bought Kenexa.”

“The last few years has seen a shift in m&a focus away from traditional Data Warehousing and BI segments towards higher growth big data… With several big data analytics companies now reaching extremely high levels of funding and growth, we believe it will be a matter of time before the largest are acquired by the major vendors such as SAP, IBM and Oracle,” the authors concluded.

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