IBM announced new technologies designed to help companies and governments tackle Big Data by making it simpler, faster and more economical to analyze massive amounts of data. New data acceleration innovation results in as much as 25 times faster reporting and analytics.
As organizations grapple with a flood of structured and unstructured data generated by computers, mobile devices, sensors and social networks, they’re under unprecedented pressure to analyze much more data at faster speeds and at lower costs to help deepen customer relationships, prevent threat and fraud, and identify new revenue opportunities.
Today’s announcement, which represents the work of hundreds of IBM developers and researchers in labs around the world, includes an industry-first innovation called “BLU Acceleration,” which combines a number of techniques to dramatically improve analytical performance and simplify administration.
Also announced is the new IBM PureData System for Hadoop, designed to make it easier and faster to deploy Hadoop in the enterprise. Hadoop is the game-changing open-source software used to organize and analyze vast amounts of structured and unstructured data, such as posts to social media sites, digital pictures and videos, online transaction records, and cell phone location data.
The new system can reduce from weeks to minutes the ramp-up time organizations need to adopt enterprise-class Hadoop technology with powerful, easy-to-use analytic tools and visualization for both business analysts and data scientists. In addition, it provides enhanced Big Data tools for monitoring, development and integration with many more enterprise systems.
“Big data is about using all data in context at the point of impact,” said Jaskiran Bhatia, Country Manager, Information Management IBM India/ South Asia. “With the innovations we are delivering, now every organization can realize value quickly by leveraging existing skills as well as adopt new capabilities for speed and exploration to improve business outcomes.”
BLU Acceleration enables users to have much faster access to key information, leading to better decision-making. The software extends the capabilities of traditional in-memory systems — which allows data to be loaded into Random Access Memory instead of hard disks for faster performance — by providing in-memory performance even when data sets exceed the size of the memory. During testing, some queries in a typical analytics workload were more than 1000 times faster when using the combined innovations of BLU Acceleration.
Innovations in BLU Acceleration include “data skipping,” which allows the ability to skip over data that doesn’t need to be analyzed, such as duplicate information; the ability to analyze data in parallel across different processors; and greater ability to analyze data transparently to the application, without the need to develop a separate layer of data modeling. Another industry-first advance in BLU Acceleration is called “actionable compression,” where data no longer has to be decompressed to be analyzed.