To turbocharge the data migration process with automation tools, focus on selecting the right tools, utilizing parallel processing and real-time replication, automating data validation and testing, and ensuring continuous monitoring. By implementing these strategies, you can significantly improve the speed, accuracy, and efficiency of your data migration efforts while reducing the risk of errors and minimizing downtime. Automation not only accelerates the process but also ensures a smoother, more reliable migration, which is critical when dealing with large, complex data volumes.

Transitioning to a near real-time ETL process requires a combination of technological upgrades, process optimization, and a shift in mindset towards continuous improvement. By implementing these strategies, organizations can enhance their data processing capabilities, leading to better decision-making and responsiveness to business needs.

BPMN Modeling the information flow again can identify additional data and prevent redundancy. Understanding the current state using the BPMN model helps accelerate data flow. Identifying unnecessary paths, loops, or slow routes can also contribute to improving the speed of information circulation.

Domain strategy must reflect the agreed project timeline from get-go and should be formally documented/maintained throughout migration. It should be developed, agreed, and published upon by all parties; client, domain owners, production owner, vendor, etc.). All data to be migrated as part of the historical uploads has to be predefined/tested to establish accurate timings (will help determine a plan for when the historical extract/uploads need to begin to ensure adequate time to migrate all data that is required to be in the database at Go Live). This process cycle requires expertise in documenting business process flows and identifying opportunities for process standardization and improvement, collaborating with subject matter experts.

Select and arrange data that can be migrated by automation in required formats and ensure its set for migration.. The precursor to this is to ensure that the new system has variety of migration options and the adapt AI tools to get it ready for validation .. Bottom line the team has to be motivated towards the end result