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Best Practices for High Volume Data Migrations

Abstract

Often part of large transformation projects, Data Migration projects usually suffer from a lack of careful planning and prioritization. As a result, every instance of a Data Migration project has cases where the original estimates of Time and Cost are revised, technical challenges discovered much later in the project cycle, and the overall customer satisfaction is far lower than expected.

What you get from this white paper

Often part of large transformation projects, Data Migration projects usually suffer from a lack of careful planning and prioritization. As a result, every instance of a Data Migration project has cases where the original estimates of Time and Cost are revised, technical challenges discovered much later in the project cycle, and the overall customer satisfaction is far lower than expected.

In this whitepaper, we discusses general approaches and Best Practices to migrate humungous data from legacy to new Stack. While this whitepaper also covers general methods to troubleshoot and optimize the performance of ETL processes and EIM, it is imperative to remember that every implementation of target stack is unique, and hence, every use of data loading is therefore also unique.

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