Simplifying data migration from the mainframe to the cloud

The mainframe market has been altered due to recent advances in automated tools for migrating legacy applications to the cloud. Many companies that rely on mainframes are now migrating to modern cloud-based platforms in order to stay relevant and ultimately, to save costs.
Firtech COO Fanie Botha | image supplied
Firtech COO Fanie Botha | image supplied

However, one of the biggest challenges when migrating from any mainframe is moving transactional and master data. These large-scale migrations normally take longer than 18 months and given the scale and complexity of these projects, businesses have been slow to adopt these automated migration tools.

Data migrations always seem simple on paper, but the reality is that 1:1 mappings end up becoming 1:n:1 mappings, with more exceptions than rules. The reasons behind this include the fact that modern enterprise systems, model data objects very differently from how mainframe systems were designed.

The fact is that many of these data migrations that are sold as being ‘automated’ end up being executed by teams of human data capturers and developers. They spend much more time on programming for the deviations in the data than the fields that can map 1:1.

Imagine if one could replace the team of human data capturers with a humanoid robot. It could be trained on exactly the same principles and exceptions that necessitated the use of humans over data migration programmes in the first place.

Digital workers are the solution

A data migration robot uses front-end GUIs to retrieve data from the mainframe and automatically migrate and capture the data into a new system. This removes any risks, where business rules that are built into the system GUI or terminal, are overwritten by the use of back-end scripts.

More importantly, it also ensures that exceptions are caught, fixed and recaptured before any data inconsistency is created in the new system. A single robot can work up to 24 times faster than a human and doesn’t need any rest or sleep. Effortless, errorless data migration in a matter of hours, not days or months.

Robotics as a service (Raas) provides business leaders with better access to the data captured in these legacy systems. Mainframe data, which contains many years of business transactions, can now be used to feed analytics or machine learning initiatives that can deliver competitive advantage.

By taking advantage of the multiple protocols and interfaces available on cloud services, they can unlock core business processes and data in their mainframe. Companies can now access mainframe data instantly, RaaS will help them move away from rigid monoliths and remove outdated interfaces and protocols.

Cloud is the future, it offers access to advanced analytics, AI, machine learning and data lakes. It also offers horizontal scalability with virtual unlimited capacity to increase scalability and elasticity.

About Fanie Botha

Fanie Botha is COO of FIRtech.
Read more: data, cloud, data management

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