Gartner Says the Future of the Database Market Is the Cloud…
“By 2022, 75% of all databases will be deployed or migrated to a cloud platform, with only 5% ever considered for repatriation to on-premises, according to Gartner, Inc. This trend will largely be due to databases used for analytics, and the SaaS model.”
Business must choose the right service for establishing robust policies and governing costs for a strong foundation. A well-designed strategy and right services will facilitate organizations in modernizing their data platforms to foster more agile and faster decision-making.
Here are some of the best practices for moving their data warehouse to the cloud.
- Plan for plan B: To prevent the possibilities of mishap, business must segment their work phases and be ready for recovering from incidents. Being hasty in unplugging old platforms can be problematic as they might be required for roll back. Based on the complexity and size of the data being migrated, the new and old platforms of the data warehouse will run simultaneously both on the cloud and on-premises.
- Improve along with Migration: It is necessary that business remediate the issues related to metadata, data modeling, and quality before migrating their data warehouse. This is primarily to avoid entailing issues of their old environment to the cloud platform. Improving the data is of high importance in the process of data management during the migration process. It is also important to do audit during migration to allow improvement and mitigating failures.
- Choose the right migration strategy: Business must consider that lift and shift of the data and old applications can bring inadequacies, due to differences between the old and new platforms in terms of performance, functionality, and interfaces. Development are essential to platform-specific components, which include hand-coded routines, user-defined functions, and stored processes. In case the data warehouse being migrated involves exhaustive tasks, reprogramming strategy can be highly effective for maximum performance on cloud environments.
- Staggering approach: The possibilities of failure are high in large-sized migration, as migrating and modernizing too much in haste bring complexity of deliverable. A migration strategy with multiple or segmented phases is less risky and accelerates achieving modernization objectives for businesses, it also allow for testing in small phases to prevent catastrophic failure.
- Testing Phase: Business must concentrate on the initial phase of their data subsets during reprogramming for a successful data migration it is where foundation are built. It is necessary that they prioritize early stages of data migration where all user groups are kept in confidence for demonstrating technical strength and adding business value.
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