Mainframe Modernization as a Catalyst for Democratized Data and Participatory Analytics

Abstract

Mainframe systems have proved to be highly stable and are being used by organizations in the banking industry, insurance industry, government, and other large-scale manufacturing systems as destination repositories, data processing systems, and mission-critical datasets. The main benefits of the mainframe use are predictability, safety, and performance, but the old architecture has limited information availability and scale of analytical ability, which can be viewed as a breadth of access to a few technical specialists. The growing requirement to use data to make decisions at all levels of the organization has resulted in the strategic concern of procuring legacy data in an accommodating manner. This article explains the capacity in which the existing mainframe migration (hybrid cloud structures, data virtualization, change data capture, and domain-oriented data ownership models) can create democratized access to data and participative analytics. Such modernization will enable the broader adoption of analytics, less dependence on qualified expertise on the mainframe, and accelerate innovation. The paper also addresses the impediments, governance, and strategic considerations that companies should consider in case they desire to apply the concept of inclusive and scalable analytics structures and simultaneously keep the integrity of data, its compliance, and the maintenance of business operations.