Guide to Avoiding Common Pitfalls in a Migrating from Teradata to a Modern Data Warehouse

Many companies are migrating from Teradata to a modern data warehouse as part of the digital transformation of their legacy, on-premise database systems. Modern databases are popular as they are cloud-friendly, highly scalable and improve data quality, availability and accessibility. However, such a migration can be a complex endeavor and migrations that are not properly planned often fail. In fact, research indicates that over 60% of data migrations fail and with Teradata migrations, the rate is often even higher. This is because Teradata is a large, highly complex system with unique SQL syntax that in some cases predates standardization. Thus the migration of massive terabytes of data with thousands of tables, proprietary elements, and specialized data types and codes requires a meticulous approach.

Here are some common mistakes that contribute to failed migrations. Take care to avoid these pitfalls and plan your migration thoroughly for a successful migration.

1. Trying to Migrate in One Quick Shot

There is often a great deal of pressure to complete data migrations quickly, usually due to budget limitations and the need to improve the performance abilities of a legacy data warehouse. However, there is a high level of risk when you take on an entire data warehouse in one shot. Such an approach has a high probability of being an expensive failure. A phased approach is far more effective – it offsets the risk of such a technically complex project and also provides faster time-to-value by avoiding a migration that grinds to a complete halt and is delayed due to technical challenges. This gradual move from Teradata requires initially offloading the most critical workloads in stages.

2. Poor Handling of Proprietary Elements

In most cases, many business applications typically have complex logic making it very challenging to migrate these workloads to a new platform. This logic is often written using user-defined functions or stored procedures, and these impact your migration as they are not portability-friendly. In case your portfolio of applications entails this type of complex code, you need to migrate to a data warehouse that complies with Spark, SWL, JDBC/ODBC, other open standards and has partners who can automatically convert Basic Teradata Query (BTEQ) scripts with macros and procedures.

3. Hasty Environment Assessment

This is one of the most critical mistakes in a Teradata migration. You must conduct a thorough evaluation of your legacy Teradata environment as the foundation for a successful data migration journey. Remember that many hours, possibly even years, of effort have gone into constructing the logic of your company’s Teradata platform. There could be a lot of junk data created over the years and tables that have been forgotten and left unused. Queries and workloads that are no longer pertinent to the business are also a form of junk. None of these objects should be moved during your migration.

Minimize the level of migration risk by leveraging an automated tool that analyzes logs from your legacy Teradata warehouse. This gives you a comprehensive understanding of your environment. Such a tool can identify what should not be migrated, and what should be migrated. It can also help prioritize aspects of migration and help you figure out how to go about a phased migration.

4. Misconception that All Cloud Data Warehouses Are the Same

When considering your new modern data warehouse, you must ensure that you pick the right one for your requirements. Perhaps managed services fit your budget, but not all cloud data warehouses offer this model. Keep in mind that while the initial cost of the cloud data warehouse can seem reasonable because you are only charged based on usage, you can be in for a surprise with a huge fee once full production workloads are underway. Another factor to consider is that performance can be slow as the number of users rises. So weigh the pros and cons against your requirements and make an informed decision.

Ensure that you select a solution that is flexible and adequately functional for your organization’s current and future requirements. Consider your compliance and privacy requirements that might make storing some data on-premises a better choice for ensuring compliance. Make sure that you have flexibility to move apps and data as required without being locked into a single vendor without the possibility of alternatives.

Why DataSwitch?

DataSwitch is a trusted partner for cost-effective, accelerated solutions for digital data transformation, migration and modernization through a Modern Database Platform. Our no code and low code solutions along with enhanced automation, cloud data expertise and unique, automated schema generation accelerates time to market.

DataSwitch’s DS Migrate provides Intuitive, Predictive and Self-Serviceable Schema redesign from traditional model to Modern Model with built-in best practices, as well as fully automated data migration & transformation based on redesigned schema and no-touch code conversion from legacy data scripts to a modern equivalent. DataSwitch’s DS Integrate provides self-serviceable, business-user-friendly, metadata based services, providing AI/ML driven data aggregation and integration of Poly Structure data including unstructured data. It consolidates and integrates data for domain specific data applications (PIM, Supply Chain Data Aggregation, etc.). DataSwitch’ s DS Democratize also provides intuitive, no code, self-serviceable, conversational AI Driven “Data as a Service” and is intended for various data and analytics consumption by leveraging next gen technologies like Micro Services, Containers and Kubernetes.

An automated data and application modernization platform minimizes the risks and challenges in your digital transformation. It is faster, highly cost-effective, eliminates error-prone manual effort and completes the project in half the typical time frame. Book a demo to know more.