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5 Challenges and Mistakes to Avoid When Migrating Off of Teradata

Teradata has been a popular and preferred analytics platform used worldwide by various organizations in the past few decades. But with increasing analytical features and low licensing costs offered by cloud services, the use of Teradata has reduced tremendously. It has been unable to provide complex analytic features essential for today’s businesses leading to Teradata migration. This migration has become vital to all organizations to efficiently adapt to today’s environmental changes and move to a better service provider that caters to their dynamic enterprise needs.

But migrating from Teradata is not a cakewalk as it involves many challenges. Though every enterprise has its strategy for migration, there can be many pitfalls that can lead to data loss, compatibility issues, or unsuccessful migration.

Hence, based on detailed research, here are a few mistakes that you should avoid to migrate off of Teradata successfully.

1. Migrating Data Swiftly

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Most businesses make a mistake by trying data migration swiftly due to budget limitations and the need to improve the performance abilities of a data warehouse. In doing so, there is a high risk of failure and data loss.

A planned and phased approach is much more effective as it reduces the risk of unsuccessful migration. Such an approach provides faster time-to-value by avoiding a migration that is delayed or completely halted due to various technical issues. This gradual approach to data migration requires initially offloading the most critical workloads in stages.

Engaging an experienced Teradata cloud migration partner can help reduce the risk associated with data loss during migration. Also, they may allow businesses to shift decades of on-premise, long-standing legacy Data warehouse and Data management ecosystems to the Cloud at minimal risk.

2. Not Involving the Team in the Process

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Not involving your team is one of the most critical mistakes in a Teradata migration, as communication is the key to a successful migration. Hence, discuss the process with concerned departments of your organizations before you begin the migration process. Communicating processes clearly will help them highlight the workflows that were thought to be obsolete and prevent any data loss.

If you don’t involve the relevant department by not taking their feedback on restructuring data, the departments may get flooded with queries regarding data loss. Whereas if you communicate with all departments, everyone gets on the same page and helps you discover the possible failures during the migration.

3. Using Inappropriate Tools

The migration process of Teradata begins with first outlining the Teradata Active Enterprise Data Warehouse (EDW) to know what can be migrated, then translating the code and migrating it to its destination. This process involves an enormous volume of SQL, SP, DDLs code, etc., and manually taking a lot of time and effort.

Selecting appropriate tools for EDW assessment, data validation, and code translation streamlines the process. These tools help save time, money, and effort and lead to fewer migration disruptions.

Among all tools, automation can be the most effective. The automation tool survey Teradata EDWs swiftly, then translate the code and allow you to work on outliners.

4. Avoiding Testing and Validating of Data

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After migrating the data to the desired cloud platform, avoiding data testing can lead to massive data loss. Therefore, testing the data is vital as it ensures that all data has been migrated accurately and will work effectively to produce accurate results.

Effective testing and validating of data ensure that all the data has been migrated to the cloud platform. The testing process involves running data through the legacy system and the cloud environment. As a result, the data should be the same on both platforms. If it’s not so, then it fails to migrate data properly.

5. Not Defining the Source Data

Defining the source data is vital to the success of Teradata Migration in the initial stages. Doing so can avoid critical failures from overlooking gaps, duplicates, and misspellings in the source data.

At the beginning of the process, define what data you’ll move and then examine it thoroughly. It is essential to clean the source’s data before the process, as cleaning it midway will lead to discrepancies and, eventually, data loss.

Defining source data is also an excellent opportunity to remove any obsolete legacy structure for users and weeding out inefficiencies.

6. Misconception That Cloud Automatically fix Everything

One big mistake you can make while Teradata migration is assuming that the Cloud will fix all problems. Though Cloud has immense benefits, including improved speed, functionality, and scalability, it can’t magically solve all problems with migration. To solve the various issues, including eliminating redundant workloads, you must scan your legacy environment before migration.


Now that you know the various mistakes you should avoid while Teradata migration, you can successfully migrate data to Cloud. Apart from avoiding the mistakes mentioned above, partnering with a reputable migration partner is also recommended.

Read also: Quantinuum Scales Error Correction To Enhance Fault-Tolerant Quantum Computing  

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