Data migration is a fundamental part of any digital transformation effort. That makes it a strategic imperative for regulatory agencies and other organizations across the public sector looking to modernize their operations. Unfortunately, the task of migrating data from disparate backed-end systems and on-premises databases to a cloud-based platform isn’t easy. In fact, it’s so fraught with complexities and risk that it’s often one of the biggest technical challenges for any implementation of a new platform.
Adding to existing technical complexities, regulators must comply with strict regulations regarding data handling. They also must remain accessible to the public, meaning that their downtime must be minimal. Further complicating matters is the diversity of data types they may have to work with, including structured and unstructured data, and in some cases even audio and video files.
For these and other reasons, data migration should always be undertaken with oversight, precision, and care. Not only is that essential for successfully navigating the six common data migration challenges outlined below, but also for avoiding delays and cost overruns, or, worse yet, compromising the success of your IT modernization projects.
Challenge 1: Identifying the right data source
Data is the lifeblood of any regulatory agency and is often highly sensitive in nature. It typically comes in different formats and from a vast network of sources including third-party vendors, internal IT departments, access databases, and manually updated spreadsheets housed on individual desktops. Navigating a tangled web of data sources and trying to figure out which ones to actually use can be an incredibly difficult and time-consuming process.
Challenge 2: Data accessibility
After identifying the right data sources, regulators need to secure access to them. If those data repositories are managed by external vendors or IT teams, that might be easier said than done. That’s particularly true if the vendor is less than motivated to help you, which could be the case for a variety of reasons, such as if your relationship is coming to an end.
Challenge 3: Data quality
Regulators overwhelmingly say that ensuring the quality of the data they need for their new platform is the most difficult part of data migration. That’s because poor-quality or irrelevant data can cause issues when it’s migrated to a new platform. The three most common types of data quality challenges regulators face are:
- Operational issues, such as when a licensee’s birth date or address is entered incorrectly, either by a person or a system. Another common challenge is when metadata deemed critical for the migration has not been extracted from unstructured documents, resulting in painstaking metadata re-cataloging.
- Silo issues, which can occur when data from various sources are migrated to a platform, often resulting in the same attributes having different values and formats.
- Compliance issues, where legacy data no longer conforms to current legislative requirements.
All of these problems are exacerbated when agencies rush to complete a data migration or opt not to work with the right partner to ensure the process runs smoothly.
Challenge 4: Mapping and transformation
Defining the proper requirements and adapting and aligning data to a cloud-based platform can be complex, particularly with legacy systems that use different data structures and standards. If your agency needs to extract data from a source system on a recurring basis, it’s important to identify a reporting and analytics strategy early in the project.
Challenge 5: Migration and testing
It’s not uncommon for issues to arise when transferring source data to a cloud platform, particularly if there are large volumes of data and short cut-over periods. To prevent this, it’s important to stage large datasets and conduct thorough user acceptance testing. If testing is not comprehensive, or if the process isn’t completed accurately and with integrity, it can lead to performance issues, missing data, and improper mapping.
Challenge 6: Security and privacy
Given the sensitive nature of the data regulators work with, the security posture of their agency is of the utmost importance. When transferring source data to a cloud platform, regulators must take robust security measures to meet sensitive PII requirements. Unfortunately, anonymizing or encrypting data can complicate the process.
Critical success factors to ensuring that your data migration efforts go to plan
Given the sensitive nature of the data regulators work with, the security posture of their agency is of the utmost importance. When transferring source data to a cloud platform, regulators must take robust security measures to meet sensitive PII requirements. Unfortunately, anonymizing or encrypting data can complicate the process.
In laying the foundation for a seamless transition of data and processes to a new platform, agencies must undertake a strategic and meticulous approach to data migration. Establishing a robust framework involves designating a dedicated executive sponsor and project manager, pivotal figures in providing unwavering support and fostering strong stakeholder alignment. Equally essential is the crafting of an agile and flexible plan delineating key phases and deliverables. The creation of a center of excellence, comprising multidisciplinary subject matter experts, adds a layer of proficiency and insight critical to the migration’s success.
Also important are effective communication strategies, comprehensive testing protocols, and a robust training program for end users further fortify the migration journey, ensuring a harmonious integration into the cloud platform. Each of these components collectively forms the bedrock for a successful data migration, underscoring the importance of strategic planning and meticulous execution.
Perhaps the most important factor to ensuring a successful migration is a strategic partnership with an experienced cloud vendor. Choosing a vendor well-versed in the nuances of data migration is crucial. They not only guide the process efficiently but also bring precision and oversight, ensuring a seamless transition. This collaboration is essential for understanding critical success factors and guaranteeing accuracy in implementing the new platform. In short, the right vendor is a linchpin for a smooth and effective data migration. Key steps they should prioritize in the data migration process include:
- Clearly define data standards: Enable the determination of overall data quality and assist in determining complexity and scope.
- Gain access to existing source systems: Ensure this is done at the beginning of the project and align existing source data with future state requirements and target schemas so that every field has a destination.
- Ensure data quality: Focus on data quality, cleansing, and enrichment as first steps in migration, as bad data increases the complexity and risk associated with migration.
- Have a well-defined data transfer process: Ensure the process is secure and properly managed for transferring data from source vendor to target vendor. Additionally, create effective test data extracts that mimic production data but anonymize the data for testing purposes.
- Participate in user acceptance testing: Ensure a keen eye for data discrepancies during this phase.
- Scrutinize your data: Pay very close attention to the transfer of documents or attachments, as these may be coming from a different system and require additional testing to ensure they are linked to the appropriate record.
In conclusion, navigating the complexities of data migration within the public sector demands a strategic approach. By acknowledging and addressing the inherent challenges discussed, agencies can pave the way for a seamless transition to a new platform. The crucial steps outlined, including defining data standards, securing source system access, and prioritizing data quality, serve as a practical blueprint for success in the evolving landscape of public sector modernization.
