Unlocking the power of data Pt.3
Legacy Systems - Outdated Data Practices & Workflows
Lee Stern
May 2, 2024
Harnessing the potential of all the data companies have at their disposal is easier said than done. Building the necessary back-end systems and workflows to do so, with the aim of delivering greater value for end users, is a challenge facing engineering teams. Often under-resourced - in terms of size, funds or their current tech stack - they're held back from delivering progress for their company through best data practice and data optimization.
In the final blog of our series on the data problems and challenges facing engineering teams, legacy systems are the topic of discussion. How do these longstanding, entrenched data systems shackle progress?
Part 3: Legacy Systems - Outdated Data Practices & Workflows
Legacy systems are a double-edged sword, offering stability and familiarity while also posing hurdles to innovation and growth. They may be the reason data can't be processed or utilised in your organisation thus impeding performance. Replacing these systems with a view of advancing the business can prove expensive and difficult with migration or integration in mind.
However, it might be necessary to change in order to keep up with industry trends in relation to data. For example, commercial property sustainability is forcing landlords to monitor their properties' energy efficiency to reduce overheads and ensure competitive profitability - this data functionality might be beyond incumbent legacy systems.
Running a parallel system that can be easily integrated with existing legacy workflows to plug the gaps may be the solution to unlock latent data. Being able to ingest data from multiple sources (including your legacy system), blend it, clean it and create customisable, robust API endpoints to specify the data called out is already achievable, but at the expense of much time and patience spent on building the system.
However, outsourcing this work to a low-code platform, which speeds up this process through automations, might save countless hours, if not days and weeks. Therefore, the burden of servicing new data and data types from new sources, on ill-equipped, older systems is reduced or eliminated.
While tackling issues arising from legacy systems often seems an impossible and a costly exercise, engineering teams can onboard value-driven solutions that add the missing strings to a legacy bow to realise data flexibility.
If any of the above challenges sound familiar to you, feel free to drop us a message so we can have a conversation. we'd love to hear from you!