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Pentaho and Big Data


Suresh Narayanappa

Pentaho Big Data Analytics provides open source reporting, data mining, and analysis, workflow and dashboard capabilities. The company’s CEO, Quentin Gallivant, made a few predictions relating to Big Data for 2014. In my next blog sometime in May am going to share a unique use case for a Big Data implementation.

The “power curve” of Pentaho Big Data Analytics will be created by the demand among business users for blending of data. Some clients of Pentaho recently elaborated on their Pentaho projects in London and NY, and it is apparent that their companies are blending relational and big data. Business clients like them are increasingly inspired by the potential to gain newer insights in blended data from a comprehensive 360 degree customer point of view, which includes the capability to analyze customer patterns of behavior and then predict the possibility of customers taking advantage of offers targeted towards them.
 
Pentaho Big Data Analytics
 
Big Data will go mainstream

From a historical perspective, projects related to Big Data have decomposed in the IT department as considerable technical skills are required to deploy them. There are also a large number of mind boggling technologies that can be mixed to construct reference architectures. Clients are required to select among the number of open source and commercial technologies, which include NoSQL databases, analytics platforms, Hadoop distributions, high speed databases and a huge number of plug-ins and other tools. Existing infrastructure should also be put into the equation, like data warehouses and relational data and the way they will complete the picture.

More innovation and interactivity

More innovations will come from the Big Data open source community. Hadoop 2.0 and other new projects related to open source and YARN, the latest generation resource manager of Hadoop, will make the infrastructure of Hadoop more interactive. STORM, a protocol for streaming communications and another open source project, will facilitate more on-demand mixing and real time information blending inside the Big Data ecosystem.

More upgrades for better analysis

The future of analytics will be characterized by new functionality, plug-ins and upgrades. This will enable faster moving, blending and analyzing relational capabilities. The ability of the adaptive data layer will be improved and secured to make it easier for clients to manage their data flows. In a sentence, technology cannot stand still to make better analysis

In the field of analytics, the simplification of discovery of data will remain unabated, thus making it easier to locate patterns and anomalies. New technologies like machine data, predictive data and also real time analytics will be ramped up into the mainstream production.


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