Data Migration may require big alterations and key details, depending on the nature of your company or business processes – covering factors like file path mapping, user credentials, and hardware settings – so a well-thought-out approach is vital.
Every well-established organization relies heavily on data to succeed and make informed decisions. In addition, this contributes to adding value to client's experience by offering and increasing revenue. However, many businesses are reluctant to migrate their data from a warehouse to the cloud for a variety of reasons, including migration time, perceived security threats, and a scarcity of experienced employees to carry out the migrations. Unfamiliarity with the new platform, a lack of migration control, and a dearth of understanding of the new platform's performance in comparison to expectations are among the other causes.
A data migration solution must address the challenges while also being quick and easy to implement. Speed and agility are the primary goals when it comes to faster time to market, high automation, low human intervention, high data correctness, high security, and lower Total Cost of Ownership.
The following are key factors to consider for any data migration tool:
- The source data model must be understood before any migration can begin. It needs to be double-checked for accuracy, and users should be able to set up criteria and generate reports. It should also help with the design of a data model, which includes things like table names, column names, indexes, and datatypes. It should be allowed to change the SQL for extraction.
- Data movement must be improved for performance using the Performance Optimizer module. This is accomplished by dividing the data files into multiple portions and utilizing all the target database's available nodes. For quicker data transit onto the cloud landing zone, data files must be compressed.
- To achieve optimum parallelism, the data loading should make use of all available resources.
- Once the data has been loaded, the data between the source and destination tables must be checked for accuracy at the table level. Comparing the row counts or checksums of each table in the source and destination tables is one way to do it.
- End-to-end governance should be included in the migration tool.
Today, we require a platform-agnostic, cloud-friendly end-to-end self-service solution that accelerates the migration of data warehouses from on premise to cloud. Kastech provides a complete solution to users, which includes the following components:
- Performing a pre-migration analysis of the existing data warehouse
- Establishing a knowledge library for scalability and target optimization
- Capabilities for data clean-up and migration
- Validating information
- Data security is ensured through encryption
- Provide a user interface that is simple to use for businesses
- Assist with data migration governance from start to finish
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