By Leon Katsnelson
By Susan Visser
By Bernie Spang
By the DB2 Guys
By Fred Ho
By Louis T. Cherian
By Shweta Shandilya
By Lawrence Weber
By Serge Rielau
By Dwaine Snow
From retailers and telecommunications companies to utility companies and healthcare providers, organizations need new ways to capitalize on the tremendous volume and variety of data that is available to them. These organizations realize that analyzing this data will be critical to producing insights that help attract and retain customers, improve operational efficiency, thwart fraud, enhance product development, and more. Unfortunately, traditional enterprise data warehouse (EDW) architectures alone cannot accommodate the diversity of analytics that organizations need to perform—which is why they need a smarter approach to analytics.
This approach must enable them to conduct multiple types of analysis—including deep, complex analysis, tactical/operational analysis, and spatial analysis—and incorporate a wide variety of data types, from structured data to unstructured and streaming data. To maximize the value of analysis, organizations must be able to apply the right level of infrastructure performance to each analytics workload and deliver results at the right time for the right cost.
For most organizations, building homegrown solutions is not the answer. Attempting to acquire and integrate all the necessary components can be a costly, time-consuming, and error-prone process. Managing those homegrown solutions might require deep expertise. Organizations need integrated solutions that simplify deployment and speed the time-to-value while streamlining ongoing management.
The IBM big data platform is helping organizations address these challenges with solutions for capturing a wide variety of data and applying a full array of analytics. Two recent additions to the IBM big data platform can help organizations supplement traditional EDW architectures, expanding the types of analytics workloads that can be run while accelerating results. The IBM® PureData™ System for Analytics enables deep, complex analytics on large-scale data volumes while the IBM PureData System for Operational Analytics provides the near-real-time analytics needed for tactical decision making.
These PureData System offerings are part of the IBM PureSystems™ portfolio—a collection of expert integrated systems that provide pre-integrated solutions that draw on years of IBM expertise from thousands of successful implementations. Both PureData System solutions work with other solutions from the IBM big data platform to help organizations capitalize on emerging opportunities from big data.
Building on the asymmetric massively parallel processing (AMPP) architecture and in-database analytics functions used for IBM Netezza® solutions, the IBM PureData System for Analytics is designed to deliver outstanding performance for conducting deep analysis on very large volumes of data. Organizations can examine billions of records and explore more variables, find more patterns, and deliver results faster than before. At the same time, the advanced I/O subsystem architecture enables the PureData System for Analytics to boost performance for mixed workloads, so organizations can conduct that deep analytics while also supporting shorter, more tactical queries.
Organizations are using this technology for their large-scale data volumes to enhance marketing capabilities, reduce churn in telecommunications, optimize digital advertising, advance medical research, and more.
The IBM PureData System for Operational Analytics is designed for organizations that need to conduct tactical, near-real-time analytics and deliver results to thousands of concurrent users, from phone-based customer service agents to retail personnel at the point of sale. This PureData System takes advantage of new IBM DB2® 10 features that enable the continuous ingest of data and support thousands of queries per second. With the PureData System for Operational Analytics, organizations can incorporate business intelligence more directly into their processes and generate actionable insights at the moment when they will deliver the greatest impact.
One global credit card provider that handles 80 million transactions per day is using this technology to support real-time fraud assessment and customer care. A natural gas supplier is gaining real-time information on changing customer demand for natural gas.
When used in conjunction with other solutions from the IBM big data platform, these PureData System solutions can expand analytics insights. For example, a utility company could analyze metering information streaming in from the grid using IBM InfoSphere® Streams to look for abnormalities that might signal network problems or indicate fraud. The company could then further analyze those tremendous data volumes with the PureData System for Analytics, using predictive analytics to anticipate fraud or using spatial analytics to locate potential network problems.
As organizations continue to realize the tremendous value of big data, they will need systems that can handle a greater volume and variety of data, conduct a broader range of analytics, and deliver results faster than ever before. The introduction of the IBM PureData System for Analytics and the PureData System for Operational Analytics demonstrates the ongoing development of solutions by IBM to meet the challenges and capitalize on the opportunities of big data.
For more information about the new IBM PureData System offerings, visit ibm.com/puredata.
IBM Big Data, Integration and Governance 2013 Forums
Attend an event near you to learn how leading organizations are making sense of massive amounts and new types of information to create value
DB2 TechTalk: Deep Dive on BLU Acceleration in DB2 10.5, Super Analytics Super Easy
Thursday, May 30: 12:30 – 2:00 PM ET
Informix Chat with the Lab: Primary Storage Manager (PSM) a Parallel Backup Alternative to Ontape
Thursday, May 30: 11:30 – 1 PM ET
Big Data Executive Summit
June 7 (Dallas) and June 10 (San Francisco)
Big Data Seminar 2013, Featuring Krish Krishnan
June 14 in New York City
Hadoop Summit North America
marcus evans Pharma Data Analytics Conference
July 10-11 in Philadelphia
IBM Smarter Content Summit 2013
Big Data at the Speed of Business
Broadcast event replay now available
Information on Demand 2013: Early Bird Registration Now Open
November 3-7 in Las Vegas