Most enterprise applications contain reference data, built into code tables, to classify and categorize product information, customer information or even internal transaction codes. This data changes relatively infrequently—but it does change over time, and given its ubiquity, synchronizing reference data values and managing changes across the enterprise is a major challenge. This e-book introduces five tenets of a solid reference data management strategy and how you can use them to build a consistent foundation for your business’s information management needs.

This Gartner's Magic Quadrant offer insight into the part of the packaged MDM solution market that focuses on how organizations master and share a "single version" of customer data with multiple views of it across their organizations - achieving a single version of master data is a key initiative for many organizations. Learn about IBM's leadership position with regard to both its Master Data Management vision and its ability to execute on that vision.

In order to get a deeper understanding of what is happening and how to influence it, access to all data, big or small, is becoming increasingly important. Data virtualization is an integration approach to provide easy access to these sources of information, including big data, on demand.

Different types of data have different data retention requirements. In establishing information governance and database archiving policies, take a holistic approach by understanding where the data exists, classifying the data, and archiving the data. IBM InfoSphere Optim™ Archive solution can help enterprises manage and support data retention policies by archiving historical data and storing that data in its original business context, all while controlling growing data volumes and improving application performance. This approach helps support long-term data retention by archiving data in a way that allows it to be accessed independently of the original application.

Speed, simplicity and affordability: 3 capabilities businesses need from their warehousing environment. IBM DB2 with BLU Acceleration gives organizations a complete, multipurpose environment to rapidly distill insight from their data, make timely decisions and capitalize on opportunities.

IBM DB2 offers multi-platform flexibility and optimized capabilities for a variety of workloads. This e-book highlights some common scenarios where DB2 helps businesses derive unprecedented value from expanding data stores—affordably and reliably.

In a world of big data and real-time information, organizations must deal with fast growing data volumes, demands for more sophisticated interpretations of data, and more rapid delivery of results. Check out the new ITG TCO comparison and see how IBM and Oracle stack up.

This white paper outlines the latest customer analytics opportunities and challenges facing sales, marketing, and customer service decision makers. It draws on IDC's research into big data and analytics (BDA) business and technology trends and provides recommendations for organizations looking to improve their customer analytics initiatives. The paper also considers the role of workload optimized systems as a technology platform to enable customer analytics and describes the IBM PureData System for Analytics as one of the leading workload-optimized systems in the market today.

Businesses around the world are looking for ways to innovate, improve customer relationships and drive down costs. But it can be challenging to find the right people and resources to support those corporate initiatives. Managed services from IBM can help.

In this far-reaching research based on analysis of over 31,000 BDA environments SIL examined the real-world impact on businesses that deploy big data analytics on a variety of platforms, including IBM’s Power, x86, competitive UNIX and a group of miscellaneous platforms. The metrics used to analyze the differences in platforms were both objective and subjective. The objective metrics include reported data points on costs, run times, resource usages, security and so on. The subjective metrics include responses on various levels and sources of customer satisfaction. Since BDA adoption is highly correlated to the success that a customer has seen in the initial stages of deployment, all of the metrics, i.e., cost, risk and satisfaction, are based on a perception of initial success. The research revealed that the platform you chose for BDA does make a huge difference. Read this report, not only to gain insights into BDA, but also to learn more about how a platform like IBM Power Systems can descrease risk, increase security, reduce costs and maximize your BDA strategy.