Preserving quality: Fundamentals of reference data management

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.
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Magic Quadrant for Master Data Management of Customer Data Solutions

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.
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Making the case for data lifecycle management – A must-have element for business transformation in a data-driven world

The ability to turn large volumes of data into insights is a competitive advantage in today's economy. To manage the data, the best CIOs are applying data lifecycle management strategies so they can:

-Fully understand what data they have, where it resides and what policies and standards exist for managing it
-Create efficient test and development environments to support application delivery schedules
-Take advantage of peak application performance
-Effectively manage data retention and access according to business compliance requirements
- Protect sensitive data

Read the whitepaper to find out how one client improved business value of their data by implementing InfoSphere Optim processes and technologies.

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Business Driven Governance: Managing Policies for Data Retention

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.
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Running at the speed of business

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.
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Customer Analytics: The Role of Integrated Systems

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.
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Don’t Let Your Shoppers Drop: 5 Rules for Today’s Ecommerce

The definition of ecommerce has dramatically expanded to include non-retail environments, with all smart businesses tailoring and marketing their products and services at the individual customer level. Meeting the increasing demands of customer-facing line-of-business applications greatly depends on the databases supporting them. This paper, written with a blend of information for the line-of-business manager and the IT professional, discusses the five key rules of great ecommerce and the changes they require in your database infrastructure.
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DataStax Enterprise Reference Architecture

This white paper outlines reference architectures for deploying Apache Cassandra™ and DataStax Enterprise (DSE) within an organization and establishes a starting point for users contemplating hardware choices to host DataStax solutions. This paper also provides guidance for system architects and system administrators during the planning stages of development, test and production environments, whether in-house or at a private or public data center. It explores common scenarios and configuration options for various deployments.
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Modernizing Data Protection With Backup Appliances

This IDC executive brief will discuss the evolution and challenges of data protection and how backup appliances can form part of a modern data protection architecture. Benefits and challenges of an appliance-based data protection approach will be discussed, as well as emerging best practices for modern data protection.
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The Evolution and Value of Purpose-Built Backup Appliances

This IDC White Paper explores the increased use and adoption patterns of PBBAs, both integrated and targeted, and the utility these appliances provide to customers in their data protection processes. In addition, this White Paper illuminates the customer value that Symantec's Backup Exec and NetBackup appliances bring to the data protection and recovery process.
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The Business Value of Managed Services

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.
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Power Boost Your Big Data Analytics Strategy

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.
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