Fokaefs, MariosHamouda, Fares2024-11-072024-11-072024-08-192024-11-07https://hdl.handle.net/10315/42477Data migration involves transferring data between systems, whether homogeneous or heterogeneous, and potentially reformatting it. With large volumes of data, resource constraints, and diverse data models and formats, migration can be critical for enterprises due to time consumption, high costs, and significant risks if not done correctly. Accurate prediction and planning for these challenges are essential for effective migration. This work introduces load testing and benchmarking for data migration to enhance decision-making efficiency and effectiveness. Our framework emphasizes extensibility and customizability for a broader range of tests. We present a prototype architecture, a development roadmap, and a case study demonstrating practical use.Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.Information technologyComputer scienceComputer engineeringElectronic Thesis or Dissertation2024-11-07Data migrationBig dataBenchmarkingLoad testingSoftware performanceData integrityData transfer