In today’s data-driven world, organizations manage vast amounts of data. As enterprises expand and grow business functions, there’s corresponding linear growth in operational data. This encompasses both master data and transactional data. While master data might change less frequently than transactional data, implementing data governance practices and defining data retention policy is crucial to maintaining data integrity and ensuring systems operate with accurate, necessary, and up-to-date data.
A data retention policy lets you define what spain rcs data and how far back data needs to stay in the transactional processing (OLTP) and outgoing data management systems. While this practice is not limited to OLTP and outbound data, the data retention policies differ from system to system and are not necessarily the same across all the enterprise functions. For instance, promotional data in retail may be needed as far back as three years to support data analytics and audit functions, whereas the order management system (OMS) may hold the orders history for just one year.
A well-defined data retention policy is crucial for ensuring compliance with legal and regulatory requirements, optimizing storage costs, and mitigating security risks. However, striking the right balance between retaining data for business needs and minimizing potential liabilities can be a complex task.