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
It’s been said that 2.5 quintillion bytes of data are generated every day and that number is only predicted to rise moving forward. In a data-rich era dominated by smartphones, Instagram and Facebook, mainframes rarely enter the technology conversation. It’s easy to forget that many of the world’s largest businesses – financial, retail, healthcare and insurance companies – still generate most of their data from the mainframe. For these companies, and many others, the mainframe is a critical source of big data that cannot be ignored.
Mainframes are the mothership of big data and store about 70% of total structured data in the world. They are the source of priceless transactional data, such as ATM withdrawals, so it would make sense that any meaningful initiative to analyze big data should incorporate mainframe information. The wealth of transactional and other types of data that live on the mainframe is simply too important to exclude.
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.
The mainframe delivers extreme performance and scalability, and that’s why it commands such a high price premium. The price of the mainframe extends far beyond just the hardware purchase – and with the operation, comes the expenses of processing and storage.
Unlike any other processing platform, the mainframe is licensed and incurs a fee based on CPU utilization. The more processing you do on the system, the more you pay. It’s based on something called MIPS: Millions of Instructions Per Second, a measurement of processing power and CPU consumption.
This eBook will guide you through the process of overcoming the four biggest challenges of leveraging mainframe data, and provide tips and best practices for bridging the gap between mainframes and modern data environments to unlock the value of all your enterprise data.
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