Managing a data warehouse migration can seem like a daunting and overwhelming task. However, storing your data in a high-performing cloud data warehouse will provide your organisation with fast access to accurate data leading to improved decision-making capabilities.

Data growth in recent years has been exponential – as has the breadth and depth of analysis departments need to perform. You need to be sure your data infrastructure can adapt to the higher volumes and velocity of data.

Even if updating your maturing data architecture feels like a monumental task, the potential for success outweighs the challenges. In this article, we touch on some of the processes to prepare for the transition and avoid surprises.

The business case for a data warehouse migration

Your first step in any data warehouse migration project should be to get clear on your business case. That is, consider what your business drivers are for making the change. Align the migration business case with key performance indicators that have been set for the overall business strategy.

For example, if your organisation seeks to increase revenue by 20% in the next two years through the development of new products and services, you want to demonstrate how a new cloud data warehouse can help you in this pursuit.

In this example, you would demonstrate how a new cloud data warehouse can collect sales and customer data and identify new upselling and cross-selling opportunities. A high-performing data warehouse will allow you to deep dive into product/service performance and adjust new offerings that better serve your customers.

The key is to be specific in your objectives and highlight how they contribute towards the strategy and create business value. Once internal teams and stakeholders understand the potential impact and value, they will be more likely to support project efforts.

Plan and architect your data warehouse migration

Having a well-designed plan is critical for a successful data migration project. To do this, you need to capture information on your current state. Identify existing documentation, the data that needs to be moved, including databases and database objects. By understanding the ‘as-is’ architecture you can begin building a project scope and more accurate timelines.

This plan also needs to identify the tools and processes that you want to use to populate and pull data from the databases. For example, ETL/ELT tools, scripting languages, reporting and visualisation tools, as well as any machine learning processes. Some cloud data warehouse platforms, like Snowflake, already offer support for a number of these processes, which can in many cases make the transition both easier and faster.

Setting an approach for a data warehouse migration

The next step should really be about uncovering your migration approach, including tasks and prioritisation/order. During this phase, you need to identify any potential issues and challenges that may arise. It is important to determine how much re-engineering you want to complete as part of the planned migration.

Assessing these two criteria will help you better understand how much time needs to be dedicated to testing. It will also give you an idea of the impact the full scope will have on deadlines and budgets.

During this phase we recommend prioritising data sets for the migration to deliver ‘quick wins’. Begin by rethinking the way that your end-users will interact with the data. Then determine what data set migration is going to be able to deliver immediate value to the business. This is essentially a pilot process, whereby you can test and validate the performance results from a smaller/controlled migration. It can help to work with a partner like Minerva, who have successfully completed this process end-to-end with multiple organisations. It is one way to minimise risk and maximise your chances of success.

Readying your data team for a data warehouse migration

Like most technology and digitisation projects, people and culture need a special focus to ensure project success. Part of preparing for a data migration is avoiding unplanned costs and mitigating risk. Including the right people from the outset is going to significantly improve your chances of a successful delivery.

Prepare your data warehouse team by ensuring that their skills and level of training allows them to perform the migration. Address the gaps in skills and experience early on, or you won’t have the right team to deliver project outcomes. Seek external help to provide insight, experience, and support if the talent does not already exist within the organisation.


Managing a successful data warehouse migration project can be approached in multiple ways. Tailor the approach based on the end-users’ requirements. Engaging an external party to ensure you cover all bases may be the best option.

Here at Minerva, we’ve worked on hundreds of data warehouse migration projects. We will ensure quick wins are realised early on through agile project management.

If you need help with an upcoming data warehouse migration, why not contact us? You can drop us email or call.


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