The significance of mainframe data is ever more apparent in our daily lives. Every time you swipe your credit card, you are accessing a mainframe; every time you make a payment with your mobile phone, you are accessing a mainframe; and of course, your social security checks are generated based on data on mainframes.
If we leave these critical data assets outside of the big data analytics platforms and exclude from the enterprise data lakes, it is a missed opportunity. Making these data assets available in the data lake for predictive and advanced analytics opens up new business opportunities and significantly increases business agility.
In this eBook, we’ll explore the challenges associated with integrating mainframe data into Hadoop, while allowing organizations to work with mainframe data in Hadoop or Spark in its native format – and how to solve them.