January 16, 2021
While the entire purpose of business intelligence (BI) is to find behavioral patterns in the data and infer future trends or actions that can benefit the business, many enterprises have been missing a key component: mainframe data. Without this precious core data, much of which is hidden in mainframe environments, BI and modern analytics won’t live up to their potential.
It has often been stated that data is “the new oil” that can power economic growth. If that’s true, then it is also true that mainframe data has been largely untapped, confined to use in traditional systems of record and given only the most limited exposure to modern analytics.
Enterprises must clearly find better ways of accessing, analyzing, and using the data they already possess. The mainframe must yield its secrets.
How Mainframe Data Got Buried
The mainframe environment has evolved with consistency for more than half a century. It’s been the rock on which many businesses built their IT infrastructure. Mainframes reliably sustained business processes, research, and even helped businesses adapt to the World Wide Web.
However, while the rest of IT has galloped toward shared industry standards and even open architectures in on-premises systems and in the cloud, mainframe has stood aloof and unmoved. It operates largely within a framework of proprietary hardware and software that did not readily share data – and perhaps didn’t need to. But with the revolutionary pace of change, especially in the cloud, old notions of scale and cost have been cast aside. As big and as powerful as mainframe systems are, there are things the cloud can now do better.
Analytics is one of those things. For example, in the cloud no problem is too big. Effectively unlimited scale is available if needed. Just as significant, a whole host of analytic tools like Kibana, Splunk and Snowflake, have emerged to better examine not only structured data but also unstructured data which abounds in mainframes.
These tools have largely been deployed on “new”…