Starting on the Right Note: Why Pre-migration Warehouse Assessment is Crucial for a Successful Migration

Migrating to the Cloud has become a must-do for most businesses for a variety of reasons. The most common advantages include improved workload performance, decreased storage costs, enhanced security, and increased scalability. However, a successful Cloud migration requires thorough assessment, planning, and execution. Many organizations rush into the implementation phase without conducting a thorough assessment, which often creates additional challenges and data loss.

A cloud migration project should begin with a thorough analysis of the current architecture, data lineage, schema, business logic, data flow, and dependencies, among other factors. This enables organizations to anticipate potential bottlenecks in the later stages and prepare for them in advance.

Why is pre-migration assessment critical?

The pre-migration assessment phase helps determine how the migration will be planned, the volume of data to be migrated, and the complexity of application relationships. The most important benefit of pre-migration assessment is that it helps identify the tables that are currently in use. This approach makes it easy to determine the migration’s priority, volume, effort, and timeline. It also facilitates the resource planning required for an efficient data migration journey.

Additionally, pre-migration assessment also helps identify data lineage. It becomes simpler to identify the relationship between a table and other code, other tables, and data that must be migrated in order to populate it in the target database. Pre-migration is crucial to precisely identify the dependent and predecessor applications to be considered.

Why data lineage is pivotal in migration

Understanding data lineage is one of the most crucial tasks during the evaluation phase. It helps organizations in understanding the scope of migration. Analyzing the warehouse’s operations allows for an accurate estimation of the scope of migration efforts.

The next step is to identify the applications that interact with the warehouse and are involved with it. It is essential to identify the lineage of various objects in the warehouse. These include the relationships between jobs and code, code and tables, tables and users, and users and reports. On the basis of data or scheduling dependencies, application groups of related objects are identified.

How Datametica’s Eagle eases pre-migration assessment

Datametica’s Eagle is an automated assessment and planning tool that automates the assessment phase that helps organizations discover unknown complexities and data lineage.

Since Eagle evaluates everything from the scheduler to the reports, it does not rely solely on the database. Eagle analyzes a data platform’s logs, scheduler, workload, scripts, and all dependencies. Automating the process saves organizations a substantial amount of time and provides an accurate report on the warehouse structure, budget, and estimated time of migration.

Eagle also helps identify and organize related objects into applications or “move groups”. It helps evaluate the migration priorities of these groups, which in turn helps with scheduling the migration steps and workloads. Eagle’s extensive and interactive user interface (UI) makes it simpler for users to search for objects, tag objects based on application name or group name, and verify the sequencing lineage, among other tasks.

Eagle takes a number of prerequisites into account, such as database logs, metadata of databases, code objects such as ETL, SQL, or shell scripts, job definitions, and so on. Eagle is packed with specialized algorithms that traverse all such data and identify the relationship between tables and code based on the queries, the code that mediates between tables, and more.

But there’s more – Eagle also fast-tracks your assessment

Considering the volume of data to be migrated and the timeframes allocated to a migration project, manual evaluation of the warehouse is not a viable option. Eagle automates the entire assessment and significantly reduces the amount of time required for this phase of the migration. In fact, Eagle generates relationship reports in a matter of just 4-5 weeks, as opposed to the manual process which takes months – and may still not be fully reliable!

With Eagle, organizations are able to commit to iterative alignments rather than restrictive up-front planning. The assessment report from Eagle enables them to provide accurate budget and schedule estimates. As an example, take a look at how a US-based healthcare services provider streamlined their Netezza assessment process using Eagle.

Conclusion

The pre-migration warehouse assessment can become complicated due to data redundancy, insufficient knowledge of data lineage, incomplete information/documentation on the existing system, complex data flow, job flow, workflow, etc. Eagle assists in bridging these gaps to conduct an effective assessment and provides accurate information on data lineage, access, user behavior patterns, and query patterns, as well as other crucial insights, to accelerate the data migration process.

Datametica is an experienced data warehouse modernization and migration partner whose automation migration product suite has assisted numerous businesses in successfully migrating to the Cloud. Reach out to our experts to learn more about Eagle and the entire product suite, and how it helps simplify the migration process.