Data on the move: Preparing for a data migration project

Moving from one house to another is a colossal task that requires collaboration and careful planning. The same is true for migrating data. In both cases, the better you prepare, the smoother the move.

In this blog, we'll unpack how to discover, assess, and prioritize data to prepare for a seamless and successful data migration project.

Fail to prepare, prepare to fail

Getting a clear understanding of your current data landscape is crucial when it comes to building a solid data migration strategy. Identifying your data's users, usage patterns, and connections with other assets and applications is essential. However, we often see teams fall into one of two traps without a solid plan: lift-and-shift or manual migration methods.

1. Lift and shift: This approach involves moving all your data as-is from one platform to another without considering your users' needs. As a result, teams end up with incomplete, irrelevant – or worse – biased data. To fix these issues, organizations then spend precious time and resources retroactively plugging holes.
2. Manual migration: Seeking to avoid the pitfalls of a lift-and-shift approach, teams often swing to the other extreme and painstakingly comb through massive amounts of data using manual processes. This inefficient method then leads to delayed timelines and high labor costs.

Now that you know the pitfalls, it's time we share how to avoid them.

Three steps toward better data migration

From our team's experience running thousands of digital transformation projects for Fortune 500 companies, we've identified the three steps to prepare for a successful data migration.

1. Data discovery: If you don't know what you're moving, your data migration won't have much of an effect. So, start by extracting metadata to build a searchable catalog of all your data assets. This step will give you clarity on the scope of your migration project. With this information, you can set realistic timelines and budget accordingly.
2. Data assessment: This step moves beyond knowing what data you have to understanding the full lifecycle of your data: where it comes from, who uses it, and how it connects with other data assets throughout the business. Determining usage patterns and connectivity gives you a clear view of your data landscape, uncovering opportunities to improve.
3. Data prioritization: Adjust your data structure and keep storage costs in check by prioritizing high-impact, high-use data for migration to the cloud. You can always archive unused data, but only after uncovering hidden relationships during the assessment phase. You don't want to get into a situation akin to moving the TV and forgetting the remote.

Partnering with experts for data migration

The scale of a data migration project can feel daunting – but you don't have to embark on the journey alone. Enterprise leaders increasingly rely on data migration software and specialists to accelerate their initiatives.

At Genpact, our data experts use PowerMe. This data intelligence platform allows data owners, data stewards, and IT leaders to make sense of their data easily and effectively by having everything in one place. With PowerMe, cross-functional teams can discover, trace, and trust their data to make decisions confidently.

Consider our partnership with one of the world's largest brewing companies. As an industry leader, the company had acquired 250 brands and managed 175 breweries in 70 countries. But rapid growth brought disconnected data between tracking materials, manufacturing, and quality control to warehousing, sales, and fulfillment.

To solve this pain point, we used PowerMe to discover and identify the most relevant data assets, automate metadata harvesting, and catalog the most critical data on the cloud. Now employees enjoy data-driven insights at the click of a button.

Data migration paves the way for digital transformation

As legacy systems become increasingly complex and fragmented – and the volume of data skyrockets – enterprise leaders might feel tempted to put data migration projects on the back burner.

But you shouldn't let data migration stand between your enterprise and its digital transformation goals.

Following our advice, and exploring the power of data intelligence platforms, you'll be ready to make a move to the future and begin transforming data into actionable insights that power innovation.