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Lifecycle management

Manage business information throughout its lifecycle, from requirements through retirement.


Improving the Economics of Information

Establish an information lifecycle governance framework for effective big data analytics


Circumvent IT Project Backlog for Efficient Operations

Consolidating and retiring applications can streamline IT infrastructure cost-effectively


Proficient Service Design and Testing Operations

Apply automation for creating, executing, and maintaining data management services


Information Governance Takes the Stage

Many organizations are hiring data scientists, but do they also need information ethicists?


Retiring Applications in the Factory of the Future

Discover how IBM InfoSphere Optim data lifecycle management effectively automates application retirement


Taming Unrestrained Data Growth in the Big Data Era

Make data lifecycle management an imperative in any big data strategy


Keeping Information Governance Agile

Discover six key best practices for planning, implementing, and assessing big data projects in a continual process


Building Confidence in Big Data

IBM InfoSphere innovation empowers end users to understand and trust their data

Avoiding database archiving can be costly

Debunking Database Archiving Myths

Think quick-fix approaches optimize costs and justify not implementing an archiving strategy? Think again

5 best practices for test data management

5 Best Practices for Test Data Management

Extract subsets of production data for continuous testing at warp speed

Back to Basics- Getting Your Information House in Order

Back to Basics: Getting Your Information House in Order

Tackle application consolidation and retirement projects to deliver more value

Getting Started with Information Governance - The Data Lifecycle Approach

Getting Started with Information Governance: The Data Lifecycle Approach

Data lifecycle management helps reduce risk, increase agility, and reduce costs