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Migrating to the Cloud Requires Automated Data Lineage Featured

Migrating to the Cloud Requires Automated Data Lineage "Sometimes you just have to look up."

Today data crosses multiple systems and platforms and has expanded to encompass every aspect of a corporation. While managing data was done manually in the past, it is virtually impossible to collect the vast amount of data across many platforms accurately when done by individuals, who are by nature error-prone. And unfortunately, if data is collected incorrectly in one area, executives tend to lose trust in the entire data process. An error-ridden report can often reflect poorly on the whole data management system.

Today, the conversation has expanded beyond manual or automated data management and has taken a drastic shift to focus on the cloud. As Gartner states, “2020 events have accelerated cloud adoption to the point where it is the de facto new normal. Enterprise architecture and technology innovation leaders should reject any new project that does not follow ‘cloud first’ as a guiding principle.” Companies realize that maintaining old legacy systems is not sustainable and they need to begin transforming to the cloud.

However, migrating from an on-prem legacy system to the cloud manually is virtually impossible and requires automated data lineage, here’s why:

  1. Planning the migration: BI developers need to understand the entire scope of a complex legacy environment to create an intelligent migration plan. What data will be taken from the legacy systems and where the cut will be made – are just a few of the questions that need close analysis. These questions need answers quickly and upfront so that a corporation can develop a clear and well-thought-out migration plan. These answers will also determine roles and responsibilities, facilitate technical considerations like code development, and help create efficient methodologies. These questions cannot be accurately answered without an automated data lineage platform that provides a full view of the complex data environment.
  2. Avoid the “lift & shift” approach: The “lift & shift” approach is a technical conversion that just shifts everything from the legacy system to the cloud. However, legacy systems often have many unused columns that were never utilized as sources and are not in reports. To improve performance and cost savings, any excess, unused column should not be migrated to the cloud. Automated data lineage will detect these unused columns and create an opportunity for a cleaner migration.
  3. Business Process Reengineering: The technology of on-prem legacy systems is different from cloud technology and presents the opportunity to update the supply chain and reengineer the business process to be efficient and rational. This process needs to be strategic and can be done so with a full view of the environment. Quick, arbitrary decisions can make it more complicated and often more costly in the end.
  4. Costs: The cloud has many different options – high cost versus low cost storage in the cloud. When understanding what a corporation needs by looking at the architecture and volume metrics in legacy systems, BI developers can plan a better distribution. When leveraging the cloud right, companies can save money. To leverage the cloud correctly, enterprises need to know their complex data environment and requirements to choose the right fit for the company.
  5. Asset Control: Early in the game, identify the assets at the most granular level that need to be migrated so BI developers can see what has already been achieved at that  level. Automated data lineage can identify assets at this level, enabling a better project plan and improved BI performance.
  6. Avoid an unplanned hybrid: When only part of the data has been migrated to the cloud and part has been left in the legacy systems, it creates an even more complex environment. Doing such creates an environment that is challenging to control and difficult to manage any post-migration issues. Without automated data lineage, this BI landscape will be nearly impossible to maintain.

Automated data lineage is a crucial part of any migration plan. It is a catalyst in creating a much clearer path to success, with better planning, control, cost savings, and with the avoidance of potential unnecessary challenges along the way.

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