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Mainframe Data for Modern Data Environments: Best Practices for Bridging the Gap

How to overcome the challenges of leveraging mainframe data in modern data environments

Processing and storage costs are two of the biggest reasons why mainframe data is not used for data intensive work.

Enterprises can address this problem by offloading mainframe data and select batch workloads— such as sort, filter, copy and more— to modern data environments that provide highly-scalable processing but with greater flexibility and lower costs.

Download this eBook to explore:

  • How to unlock the value of all your enterprise data
  • Steps for overcoming the four biggest challenges of leveraging mainframe data
  • Tips and best practices for bridging the gap between mainframes and modern data environments