Top Data Migration Risks and How to Overcome Them

Whether you're moving data to a new ERP system, to a CRM, or migrating it to a more cloud-based infrastructure, transferring your data is not a simple “lift and shift.” A successful data migration depends upon certain preparation work. Brush up on some of the common challenges associated with migrations to keep your project on track, on time, and on budget.

The Most Common Risks when Migrating Data

1. Data Loss
Traditional migration approaches don't put data quality checks at the center of their strategy. This design puts all of an organization’s valuable data at risk of being lost forever. Data loss happens when source data is deleted before you can confirm the validity of the data at the destination. The loss might be unrecoverable if you don't have access to the source data, but the impact on your data migration will be irreversible. Instead of the “all or nothing” approach with “lift and shift” migrations, data quality checks before and during a migration ensures only the most up-to-date and accurate data gets moved.

Enterprises these days operate with some pretty complex infrastructures when it comes to the software and tools that interact with their data. Data is constantly being analyzed and routed back and forth between the cloud and on-prem devices and across the business. Data migrations that risk prolonged downtime disrupt the business and cost time, staff, and revenue. An improper data quality strategy increases the likelihood that excess downtime will be needed to configure systems to take on multiple data sets.

Data mapping is a crucial component of data migration. Moving data from one database to the next more than likely involves large data sets (changing in real-time, mind you) whose schema and formats don’t line up. Accurate data mapping—really the only kind you’d ever want—can be extremely resource-heavy. Records have to be compared individually unless the software is built to withstand that kind of power.

Data governance defines the rules and policies for how individuals and groups access data and the kind of access they are allowed. But consider the sheer number of sources and destinations the average enterprise juggles, and it’s easy to see how quickly permissions and privacy conflict. It’s one of the reasons the use of data catalogs as a sort of “data directory” has become a core feature of successful data migrations in recent years. Data catalogs allow users to easily find and trace data. Combined with data and metadata management, data catalogs provide enterprises with an easy way to see where data has been gathered, stored, processed, or removed to better maintain governance controls.

Compliance With Privacy Regulations

Anytime data crosses a firewall— like during a migration—security and privacy controls are put at risk. Maintaining regulatory compliance throughout a migration is especially critical when handling sensitive customer data, as in healthcare or financial industries. Utilize data catalog and governance tools throughout your migration to maintain visibility into your data and meet regulatory guidelines.

How to Prevent Data Migration Risks

Ultimately, every data migration has an element of risk, so what can you do to ensure your data migration is successful? Here are three ways you can do more.

Put data quality efforts to the forefront of your data migration effort in order to identify issues early and avoid costly project downtime. Believe it or not, your goal - and it is possible - should be 99+% data quality by the time of go-live. The key to a successful data migration rests largely on how successful your data quality strategy is, so frequently inject data cleansing measures into the migration path.

2. Work With a Unified Data Management Platform

Unified Data Management platforms consist of tools across multiple data management disciplines, making data migrations a breeze with everything you need right at your fingertips. From migration to quality, data governance to data catalog, and even data matching and integration tools, tedious tasks are automated, and data loss is mitigated.

Automation is critical when going through a data migration. Many organizations are moving massive amounts (hundreds of terabytes or petabytes) of data. Manually checking that data is incredibly time-consuming and tedious without the right tools. That’s where automation comes in. Automation tools help with data matching, data mapping, and metadata scanning to ensure your data is error-free and aren't corrupt. AI functionality ensures that these tools deliver these results with more than 99% accuracy and efficacy. They ensure you can find and correct errors before they threaten your data migration initiative.

Data Migration: Solved

Handling large-scale data migrations is a big task; having the right tools and team supporting you is critical for success.

These days, it’s easier than ever to avoid common migration failures. New approaches to cloud-based data management platforms have migration best practices baked right in, reducing risk and budgetary waste. What’s more, these platforms extend the benefits of data migration and allow enterprises to safely reassess how their data flows through the organization without incurring extra costs.

To learn more about achieving faster data migrations and reducing cost and downtime, check out this IDC Business Value Study.