7 Gaps in Data Migration | November Good Bits
Nearly all companies we talk to these days are adopting a data and analytics strategy that incorporates cloud technology. Some are going all-in on cloud and others are exploring opportunities to move non-critical data sets or applications to the cloud as an initial step.
For those that are looking to quickly take advantage of cloud benefits, migrating on-premise data to the cloud provides a good starting point. From our experience in helping our clients with large-scale data migrations, we have identified a number of key factors for determining the best approach.
Seven factors we have observed that are often overlooked in the planning stage but can have a considerable impact on the success of the migration include Throttling and Elasticity, Efficient Data Validation, Automatic Configuration and Scheduling, Fault Tolerance and Restartability, Upserts for CDC, Generate/Respond to Events for Integration, and Data Type Support.
We recommend that these parameters be considered in your assessment phase so that your implementation runs smoothly, or at least you are better prepared. For a complete overview of these parameters and a solution to fill the gaps, read our blog post on Practical Challenges of Large-Scale Cloud Data Migrations.
Nov 28 (Live in UK) – Hydrograph 2019 – Building Data Pipelines
for Cloud, Streaming, and Other Updates
Join Our Team
Open position in USA – Java J2EE Developers