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Overcoming the challenges of integrating legacy data

Written by Fri 28 Jan 2022

Data may be the lifeblood of many modern companies, but those enterprises that have valuable data stored in disparate silos across the business will fail to make the most out of this valuable resource. While integrating legacy data can be a complex undertaking, it can also unlock a great deal of benefits for companies.

Many innovative and cutting-edge technologies that make use of real-time analytics to provide actionable insights from data require a comprehensive view of all the data held by an organisation, if it is to be as successful as possible. Legacy databases can also represent data risks, due to the use of out-dated security, and are often incompatible with new technologies.

No one-size-fits-all approach exists that is suitable for all companies when it comes to integrating legacy data and systems. However, according to research from analyst firm Gartner, once a business has evaluated legacy systems and has a clear understanding of what they want to gain from modernising them, finding the right approach becomes more simple.

“Ultimately, modernising legacy applications means choosing between rearchitecting, rebuilding or replacing,” says Gartner in a blog post. “Rearchitecting has medium costs and risks, whereas rebuilding or replacing provides best results with higher costs and risks. The key is to weigh all options to help identify the extent to which each will have the desired effect — with the minimum effort and maximum positive impact.”

For some companies, legacy data would benefit from being migrated to a cloud environment and others may find that converting outdated file formats into more up-to-date formats can make the transition quicker.

There’s no question that legacy systems are becoming increasingly obsolete and there is no better time to extract the data from these locations and incorporate it into a modern and streamlined data platform that will be able to be used for years into the future.

Written by Fri 28 Jan 2022

Tags:

Big Data business data integration legacy legacy data
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