Open source tools and solid business processes will unlock the true potential of big data analytics, according to data integration and business analytics firm Pentaho.
Wael Elrifai, EMEA director of enterprise solutions at Pentaho, said in an interview with V3 ahead of the V3 Big Data Summit that the evolution of software tools used for data analytics will have open source frameworks and code at their core.
The reason for this is down to the speed at which data analytics are evolving, which makes it difficult for companies working on their own tools, based on siloed technology, to provide cutting-edge software.
"In terms of evolution the tools are moving fast and the changing landscape makes it difficult for different tools to keep up, which is actually where it becomes very important to have this open source ecosystem not just for underlying Hadoop infrastructure but for the data integration infrastructure," he said.
Elrifai explained that creating tools that use open source frameworks allows companies to tap into a vast global community of coders and developers adding functionality and capabilities to the base frameworks.
Pentaho's own use of open source in its products has allowed the firm to develop its software offerings significantly faster than rival companies that use their own technology.
"We're able to stay up with the times because we're open source," he said. "As a result of that we're making major releases every six months; we have genuine new functionality every six months."
Elrifai also noted that software firms can add significant functionality to open source frameworks buy creating more user-friendly interfaces on top of the basic foundations.
Bringing business into data analytics
The systems and software for data analytics are evolving at a heady pace, but Elrifai pointed out that companies wanting to make the most of them need to put management and business process in place to react to the insights and recommendations produced by big data analytics.
"When you do predictive methods or maybe prescriptive analytics, you're getting feedback from support systems. You still have to have a management process to implement [changes]," he said.
Elrifai warned that, while companies may use data analytics to keep up with trends in the enterprise arena, they need to consider the business case of setting up such systems and consider what they want to achieve with an investment in analytics.
Failing to take this approach runs the risk of encountering a culture of ‘me too' where adopting analytics is the done thing, rather than a clear business-driven decision.
Elrifai pointed out that this need is particularly pertinent with the use of predictive analytics, where companies crunch big data in near real time to ascertain when an event may take place, such as a component in a vehicle failing. Without processes that allow predictions to be acted on, the investment in such systems becomes void.
"If you've built a real-time predictive system and you don't have a management process to implement those recommendations, that's not going to give you much utility," he said.
So while there are plenty of cutting-edge analytics software tools available to enterprises, taking the time to consider how they are best used could be the difference between driving clever data-led business decisions and ending up with a redundant system.
For more insights into how big data join V3 for our Big Data Summit from 3 - 5 November and sign-up for our live webinar featuring Pentaho and Accenture to discuss how to make the most from big data.
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