Data lifecycle management means planning and building architecture for data integrity around all of these stages to make sure they are functioning optimally and reaching their expected outcomes. Additionally, data lifecycle management is important for delivering on several key functions and responsibilities of your DataOps team, including regulatory compliance and data interoperability.
With varied data collection points that could number in the millions, data lifecycle management helps data functions create and maintain interoperable data architecture that reduces friction and improves the usability of all collected dataflows.
An effective data lifecycle management plan is one that allows your data function to deliver on everything that is expected of it at each stage of the data’s lifecycle while also minimizing organizational risk by adhering to data regulations and ensuring data security best practices. Creating the best plan for your needs requires some core features to ensure it works as expected now and in the future. These include: