Pentaho and EMA Reveal Big Data Priorities for 2014

ORLANDO, Fla., Oct. 24 – Delivering the future of analytics, Pentaho Corporation today announced that it has identified four priorities for big data analytics innovation based on end-user research at Enterprise Management Associates (EMA) and 9sight Consulting – “Big Data: Operationalizing the Buzz” and from early adopters working closely with Pentaho. Trends strongly indicate that as customers move from pilot implementations into big data production, the focus shifts to solving challenges such as blending data, predictive analytics and real-time query optimization.

According to this year’s Big Data survey, big data implementations in production rose from 27% in 2012 to 34.3% this year. In addition, 68% of companies are running two or more big data projects as part of their big data initiatives. The top three big data business drivers include: speeding time for operational or analytical workloads (39%); increasing competitive advantage with flexibility of data used in business solutions (34%); and business requirements for higher levels of advanced analytics (31%).  For companies with an analytics strategy in place, the top business driver was the need to combine sales information into operational analytics (57%).

Four Big Data Innovation Priorities

The findings suggest that those actively involved with big data projects have moved beyond concerns typically associated with operational BI and are now focused on solving complex data management and analysis challenges. Pentaho is working with early adopters of big data such as BeachMint, Shareable Ink, TimoCom and Travian Games to address these challenges by innovating in four key areas:

• Data blending for hybrid data architectures – as companies move into production, businesses need to access different types of data sources held in different systems and blend them without losing data integrity including big data sources. Most common business problems can then be tackled, including fraud detection and risk management. Companies can blend big data at the source today in Pentaho 5.0.
• Real-time analytics on Hadoop – the ‘need for speed’ revealed in the EMA/9sight research is confirmed by Pentaho customers demanding support for Storm, a real-time ETL technology. Pentaho for Storm emerged from Pentaho Labs to enable developers to process big data in real time using their existing visual ETL transformations.
• Predictive analytics – Taking advantage of batch processing in Hadoop can help businesses make more accurate predictions leveraging big data for fraud detection, upselling and a range of predictive applications.
• Free Form Search (SolR, Cloudera Search, Apache Search) – Companies seeking new discoveries from corporate and big data sources can use fast and flexible search technologies.  Business users don’t need to know SQL, they can run Google-like searches based on intuition to initially query data, before performing more complex blended data queries.

Pentaho remains at the forefront of the big data ecosystem with more than 200 customer implementations, a 100 percent increase in big data bookings year over year and a growing number of big data partnerships such as MongoDB, Rackspace,Splunk, Intel, Xyratex and Think Big Analytics announced in 2013. Customer examples include edo interactive, an online venture that uses Pentaho running on Hadoop, Hive and HBase to analyze more than five billion consumer transactions in real-time to improve targeted advertising; Paytronix, which uses Pentaho for Integration and big data blending pulling data from Hadoop to improve customer loyalty programs for 8000+ restaurants across the US; and TravelTainment, which embeds Pentaho into its software for travel companies, giving them better insight into big data sets from Hadoop for planning promotions and other services.   

According to Richard Daley, Chief Strategy Officer, Pentaho, “In 2013 we’ve seen customers and prospects moving beyond single Hadoop deployments to hybrid data systems that might include Hadoop for scalable storage, and MongoDB for high speed front-end analysis, STORM for real time analytics, and an engine like Cloudera Search or Apache Search for quick data look up. These customers turn to Pentaho because we provide a proven data integration and analytics layer that can work with all these technologies as data flows through the hybrid environment.”

John Myers, big data analyst at Enterprise Management Associates states, “As the results from the EMA and 9sight Consulting report, “Big Data: Operationalizing the Buzz” points out, we are entering the era of Hybrid Data Ecosystems where relational, structured data must be able to interact with non-relational data. Organizations have multiple data platforms and more sophisticated users. As they begin to mash-up information in these new multi-structured data platforms, ecosystems management, data access and integration and data analytics become much more important.”