Most data teams misuse OLTP and OLAP systems by forcing mismatched workloads, leading to bottlenecks, high costs, and missed opportunities. Smart teams separate environments, optimise data flow with incremental syncing, and use safe migration tools like Mirror Mode to achieve both transactional efficiency and analytical power without disruption.
Most data teams struggle because inefficient architectures force them to choose between fast transactions (OLTP) and powerful analytics (OLAP), creating delays, high costs, and frustrated users. Smart teams separate systems by purpose, use efficient syncing like Change Data Capture, and adopt performance-based pricing to achieve real-time insights, cost savings, and scalable architectures without disruption.