The RDBMS Split Process: A Practical Guide to Streamlining the Transition to Data WarehousesBy Ohad Sheory on February 5, 2025
In the first part of this series, we explored how harmonizing relational database management systems (RDBMS) with data warehouses (DWH) can drive scalability, efficiency, and advanced analytics. We discussed the importance of aligning these systems strategically to balance their unique strengths while avoiding unnecessary complexity.
In this installment, we tackle a challenge many organizations face: fostering the smooth transition from an RDBMS only to a hybrid system that incorporates both RDBMS and DWH. This process is critical for mexico rcs data unlocking a data ecosystem’s full potential but comes with its fair share of risks – data quality, correctness, downtime, and synchronization hurdles. This article outlines a roadmap to streamline the migration, minimize disruptions, and establish a scalable foundation for future growth.
Phase 1: Planning the Data Split
A smooth transition begins with thoughtful planning. Deciding where each piece of data belongs is crucial for a seamless split:
Categorize Data: Start by dividing data into categories, such as “customer-oriented” (high-volume) and “non-customer-oriented.” This categorization guides migration priorities.
Minimize Dependencies: Analyze table JOINs to identify and minimize cross-group dependencies, simplifying synchronization between the RDBMS and DWH.