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

Mainframes: The Original Big Data

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.

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.