{"id":8492,"date":"2022-01-11T14:15:13","date_gmt":"2022-01-11T14:15:13","guid":{"rendered":"https:\/\/wealthrevelation.com\/data-science\/2022\/01\/11\/mainframe-modernization-making-it-happen\/"},"modified":"2022-01-11T14:15:13","modified_gmt":"2022-01-11T14:15:13","slug":"mainframe-modernization-making-it-happen","status":"publish","type":"post","link":"https:\/\/wealthrevelation.com\/data-science\/2022\/01\/11\/mainframe-modernization-making-it-happen\/","title":{"rendered":"Mainframe Modernization: Making It Happen"},"content":{"rendered":"
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In the fast-paced world of technology and business, it can be hard to keep up with what\u2019s new. What\u2019s new today can be obsolete in a few weeks, and adapting to this ever-changing landscape can become a challenge if an organization isn\u2019t well prepared or equipped. Modernization of systems doesn\u2019t necessarily mean transitioning to an entirely new system or platform; often, all it takes is actual modernization of existing tools to help them adapt to new business demands and requirements.<\/p>\n

The mainframe is one system that has stood the test of time. A number of naysayers taut the system as \u201clegacy\u201d or obsolete, but the fact that mainframes handle 68% of the world\u2019s production IT workloads<\/a> indicate otherwise. Mainframes are proof that the latest isn\u2019t always the greatest, standing firm as one of the foundations of business systems in today\u2019s most successful businesses around the world. What some don\u2019t realize is that the race toward digital transformation is not reliant on the system or platform an organization has in place; digital transformation initiatives rise and fall depending on how they approach data. Regardless of the platform used, data analysts who work with irrelevant or stale data are prone to achieve false or misleading results. Access to real-time data is key, and data gathered days or hours\u2014even minutes\u2014ago isn\u2019t a current representation of the current situation. This can lead to an organization acting on miscalculations and opportunities that no longer exist. Actionable insights need to come from real-time data to ensure that your organization can make sound business decisions in a timely manner.<\/p>\n

The Old vs. the New<\/b><\/h3>\n

Conventional methodologies have kept mainframe data and real-time data separate due to issues with accessibility. Most businesses traditionally use Extract, Transform, and Load (ETL) processes for data analysis, a logistically complex and time-consuming process that\u2019s prone to errors and stale data because it\u2019s performed only periodically. This can lead to hours or even weeks of delay that\u2019s simply unacceptable in today\u2019s always-connected, always-on digital business landscape. Today\u2019s businesses depend largely on real-time business intelligence\u2014and access to it\u2014to get a competitive edge.<\/p>\n

In light of this perceived separation between mainframes and real-time data analytics<\/a>, data scientists have found that the creation of analytic models can be too slow at times due to the conventional process of offloading data from the mainframe to other platforms for analysis. Organizations should move away from ETL processes and find ways to make real-time data analytics from the mainframe quicker and more efficient for their business. Mainframe modernization<\/a> is key in making mainframe systems work with modern solutions because it allows for data virtualization, integrating all disparate enterprise data into a logical data layer. This layer manages the unified data and provides centralized governance while delivering the required data in real-time to business users.<\/p>\n

Depending on the industry, mainframe modernization can optimize key business processes like order processing, payment gateways, and internal business operations queries. Mainframes are known for performing high-volume transaction processing, and these transactions can make or break a business. Managed in real-time, it will help organizations battle fraud and manage business risks as they arise, or even before they do. The data gathered can also help paint a more accurate representation of who a company\u2019s customers are, allowing them to better plan resources and come up with more personalized initiatives.<\/p>\n

Making IT Happen<\/b><\/h3>\n

Mainframe modernization is a major undertaking that presents a host of options for every organization. These options will vary depending on a number of factors, including business size, tenure, and industry. The following, however, are a few of the key considerations in modernization.<\/p>\n