Most of today’s industries require the ability to store data while simultaneously allowing end-user access. However, the modern concept of a database hasn’t always been the main technology used to store data. A wide selection of alternative methods has been used over the years to store and retrieve data, such as record management systems, indexed files and even the old good flat-file approach.
The result is that a lot of this data is trapped within old data storage technologies that cannot handle the needs of 21st century technology. For example, more than 75 percent of the world’s business data is still being processed in COBOL — a programming language that many of today’s developers may scoff at, but that thrived in the past for its fast, and efficient data storage system.
Although old and much less-used than other programming languages, COBOL is time-tested and currently thriving in many enterprises. For instance, many government and health agencies (as well as numerous others) continue storing important data such as Social Security or health records written in COBOL inside these aging databases.
So why is this a challenge for IT? Well, while COBOL may be great and work well for these industries, in today’s mobile-enabled world, most company executives need to access such vital information at the tip of their fingers — something that most aging COBOL applications can’t allow.
Plain and simple, sometimes old technology is not compatible with new technology. As such, many companies have gone the popular route and completely rewritten their applications simply to be able to gain access to their data stored in legacy formats or databases. This process can be extremely time-consuming and often very costly, but worst of all, it is very risky.
The situation poses a question: if the existing applications are working fine, are test-proved and have competitive advantages that would be lost in case of a modernization, why change all that just for the sake of being able to access the data? If the problem is the data, a much better approach is to focus on the data, instead of the applications. And this is effectively happening.
To avoid these shortcomings and make life easier on themselves and their wallets, companies are increasingly considering a database modernization — a phased migration process — instead of tearing down or replacing their existing systems (like COBOL) that may work well for them, but need to be brought into the 21st century.
By deploying an approach where modern APIs are placed over the legacy data, there is no need for application changes (which eases the minds of many IT managers). In fact, by migrating data in a phased process, companies ensure less chance for data corruption and loss, see fewer capital costs and continue running their applications with no downtime. When all is said and done, companies have access to data now available on their mobile devices when needed.
Database modernization should be an evolution, not a revolution. A well-thought-out migration plan is an excellent start. Since modernization projects are rarely seamless, it is important to take the time required to perform testing before going live.