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What is data lifecycle management?


Data lifecycle management is the process of managing business information throughout its lifecycle, from requirements through retirement. The lifecycle crosses different application systems, databases and storage media. By managing information properly over its lifetime, organizations are better equipped to deliver competitive offerings to the market faster and support business goals with less risk.

  • Forrester Consulting Total Economic Impact Study

    Forrester Consulting Total Economic Impact Study

    IBM InfoSphere Optim Solutions for Data Lifecycle Management
    Get the analyst report

The emergence of big data creates growing amounts of data, only reinforcing the need for effective data lifecycle management. Big data is more than just information stored in an Apache Hadoop-based framework; it is also the structured data within data warehouses, databases and standalone applications. In addition, there will be a greater need to speed delivery of big data applications, requiring organizations to create realistic, right-size, masked test data. In the world of big data, all sources are crucial and must be managed throughout their lifecycles.


As organizations look to big data environments to analyze and manage critical business decisions, they will face significant challenges related to data lifecycle management:


How Data Lifecycle Management helps your enterprise

Data Lifecycle Management solutions from IBM InfoSphere help address these challenges by:


Customer Spotlight


  • CSX. How tomorrow moves.

    CSX Corporation

    CSX is improving application testing, protecting sensitive data and managing data growth across both mainframe and distributed platforms. "We can now easily engage third party contractors to conduct tests knowing that our data is secure."

    Read the case study. (PDF, 651KB)