Maximizing the Power of Analytics for Big Data

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.

Conducting deep analytics on large-scale data volumes

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.

Enhancing tactical analytics and delivering near-real-time insights

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.

Bolstering additional big data solutions

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.

Expanding analytics capabilities

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.