Teradata Migration: A Step-by-Step Guide Backed by Healthcare Customer Success

Learn how a large healthcare organization cut costs by 60% while seeing an 85% increase in query efficiency by moving from Teradata to Snowflake—and how you can do it too.
April 3, 2024
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A tsunami of cloud migrations is about to hit the healthcare industry. According to Hakkoda’s Healthcare State of Data report, 74% of healthcare organizations intend to centralize on a cloud platform in the next two years. The mounting obsolescence of legacy data systems, paired with the growing benefits of a centralized cloud platform like Snowflake for advanced analytics and AI use cases, mean that there has never been a greater time for your organization to consider the benefits of a Teradata migration. 

Catching that wave of new cloud arrivals, however, will likely require the assistance of Managed Service Providers, Systems Integrators, and IT consultants. 84% of healthcare organizations acknowledging the need for a moderate to large amount of external help modernizing their data stack. 

Data leaders in the healthcare space will also be encumbered in their modernization efforts by unique industry challenges, including the complexities of working with Epic data and the intricate labyrinth of privacy and security requirements surrounding patient information. The plus side? Migrating to the cloud will pay off big for healthcare organizations in the long run while helping them lay the foundations for AI use cases and implementations

In this blog, we will take a 7-step approach to planning and implementing your Teradata to Snowflake migration. We will also share a success story from a large healthcare organization that saw a 60% cost reduction after migrating. 

Step 1: Identify the Goals of Your Teradata Migration

Before a successful migration from Teradata to Snowflake can begin, stakeholders at your organization should align on key outcomes and objectives for the migration. Not only does this allow you to find alignment on what your organization hopes to accomplish by migrating, but it will also help you assess the success of the migration project when it is completed.

Some of the most common reasons healthcare organizations may migrate from Teradata to Snowflake include:

  1. Retiring Expensive Legacy Technology. On-premise systems like Teradata are often inefficient, siloed, and costly to maintain. Centralized cloud platforms like Snowflake, which uses a consumption-based billing model, give organizations better visibility and control over their spending while reducing maintenance expenses.
  2. Breaking Down Data Silos and Unlocking Efficiencies. For many healthcare organizations, electronic health records (EHRs) are just one piece of a larger patient story. For organizations still on legacy data systems, troves of clinical and non-clinical data often reside in silos that block insights across the patient lifecycle. A centralized cloud platform provides a single source of truth capable of integrating data from multiple sources and scaling with your organization. 
  3. Integration with Other Tooling. Legacy data systems often lack the necessary integration capabilities to connect with other critical systems and tools. This can cause difficulties when organizations grow or merge into larger healthcare systems, creating additional data silos and interrupting mission-critical workflows. It may also lock organizations into using vendors and tools that are not a strong fit for their needs.
  4. MLOps and AI Use Cases. 65% of healthcare orgs believe that GenAI will be very or critically important to their success by 2027. These organizations also understand that, in order to capitalize on the wealth of emerging AI developments, they must first climb their way out of a state of data chaos and into a flexible, interoperable, and well-governed centralized data platform.
  5. Compliance, Governance, and Security. Finally, it is worth highlighting the robust suite of built-in security and governance features native to the Snowflake Healthcare and Life Sciences Data Cloud. In a tightly regulated industry like healthcare, these features are instrumental to keeping sensitive information private and secure in an increasingly hazardous digital landscape. 
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Step 2: Developing an Execution Plan

Once your organization has settled on the primary goals of the migration, the next step is to identify some of the obstacles that may stand in the way of success. Common challenges include: 

  1. Prioritization. What is your migration timeline, and what data gets moved to Snowflake first?
  2. Data Talent. Does your team have the skills and experience to facilitate the migration from Teradata to Snowflake? What external help will your teams need to guide the migration effort?
  3. Budget. How much will the migration cost? Will the workloads you migrate have strong returns on your investments? 
  4. Security and Governance. How do you keep data secure during migration? How do you set up a data governance framework post-migration to ensure long-term data quality?

Once you have identified both goals and challenges for your Snowflake migration, you will need to develop an execution plan. This plan should include a migration timeline, proposed resource allocation, and a well-defined rubric for what a successful migration will look like. This rubric can focus either on the alleviation of pain points and cutting costs associated with your existing data infrastructure or on delivering new value to your organization, whether that’s by monetizing your data on the Snowflake Marketplace or building a foundation for advanced analytics and GenAI applications.

Step 3: Taking an Inventory of Your Existing Data Assets

Before your Teradata migration can begin, you need to define the scope of your migration, which may consist of a single database or of multiple databases spread across one or more data platforms. 

A successful migration starts with a comprehensive assessment of data volume, quality, and integration capabilities, which will also make it easier to prioritize which data sets you move first to maximize uptime and prevent disruptions to mission-critical operations. 

You may also use this opportunity to benchmark performance and map user roles, making it easier to test performance improvements post-migration and streamline the provisioning process in Snowflake, respectively.

Step 4: Preparing Your Data for Migration

While migrating to a centralized cloud platform can help resolve many major pain points for your organization, the success of your Teradata migration will depend on the extent that the data you move is both complete and accurate. 

To avoid frustrating setbacks in your migration timeline, you should dedicate the time and energy up front to identify and eliminate duplicates, inconsistencies, or errors in your data. 

Clean, quality, and well-governed data is also foundational to getting your organization AI-ready

Step 5: Migrating Your Data to Snowflake

Now that you’ve drawn up an execution plan and prepared your data, you can begin the migration in earnest. First, this means migrating your database structure into Snowflake. This can look like a simple “lift and shift” migration, which directly transfers existing logic from one data platform to the other, or involve re-architecting your data with improved models and logic that differs from the source dataset. 

Once a database structure is in place, it becomes possible to initiate either a bulk or staged migration of your data. Often this step in the migration process will start with an agile move of your most mission-critical data to reduce operational disruption. 

Step 6: Performance Testing and Validation

After your data has been safely and securely ingested, it’s time for validation, checking that data is transferred both accurately and securely into Snowflake. This is also the optimal timeframe to test query performance against the benchmarks you collected in Step 3, fine-tuning as necessary to optimize your Snowflake environment. It is recommended that you continue to run both Teradata and Snowflake in parallel during this phase, during which rigorous testing can identify any issues that might not have been evident during migration.

Once all of your data has been migrated and performance testing and optimization have been completed, you’re finally ready to decommission Teradata.

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Step 7: Training and Team Enablement

Now that your Snowflake environment is up and running, the final step in a successful migration is to enable your internal team for ongoing success and innovation.

The enablement process includes providing comprehensive Snowflake training to your teams, ensuring that employee stakeholders understand the benefits of the platform and the reasoning behind the migration, and demonstrations of how Snowflake can support daily workflows, power cutting-edge tools, and inform mission-critical decisions. 

Customer Success: How a Large Healthcare Organization Slashed Costs by 60% Following a Teradata Migration

Now that we’ve walked through the stages of a successful Teradata migration, it is useful to illustrate just what a successful migration looks like. 

A large healthcare payer came to Hakkoda with the need to migrate more than 2 Petabytes of data in 12 different databases from Teradata to Snowflake. The organization had encountered major bottlenecks in their in-house migration efforts, where manual migration processes were costing the organization 96 hours across 3 people each week. 

Hakkoda was tasked with helping to alleviate the significant labor costs associated with the project while helping the organization achieve its initial goals of improving query performance and slashing data management costs. Our Healthcare and Life Sciences team introduced a prioritization system that migrated the largest data tables first, which gave the customer a fully functional dashboard that could be used to test and optimize queries in real-time, even mid-migration. This in turn provided the customer with a better idea of their return on investment, reassuring key stakeholders throughout the organization that the move to Snowflake would have long-term advantages for their bottom line.

By the end of the 8-month engagement,  over 700 queries had been successfully migrated and Teradata was fully decommissioned. The customer saw a 60% reduction in data management costs and achieved an 85% increase in query efficiency on Snowflake when compared to Teradata. They also saw a 16x boost in testing speed.

Completing Your Teradata Migration with Hakkōda

With the majority of healthcare organizations looking to make the jump to a centralized cloud platform in the next two years, there has never been a better time to evaluate the benefits of migrating from Teradata to Snowflake. Organizations still wary of embarking on their cloud migration journey, meanwhile, can take solace in knowing that, like many of their peers, they won’t need to make that leap alone.

Hakkoda’s healthcare and life sciences team is built on years of industry experience, bringing veterans from top healthcare organizations together with scalable teams of SnowPro-certified data experts who know how to help your organization reach its data goals without getting snared in industry-specific challenges. Our teams also come equipped with industry-tested Solutions and Accelerators built to supercharge data migrations, drive patient-first outcomes, and deliver faster returns on your data technology investments.

Ready to retire legacy tech debt and start innovating in the cloud? Let’s talk.

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