Data migration plays a critical role in digital transformation initiatives of a business, which in turn helps companies to tackle competition with improved efficiencies. The data migration process is a complex exercise that demands careful planning, technical expertise and sound understanding of business objectives.
Data migration challenges can escalate quickly and result in extended downtime, data loss and most importantly, compliance issues. Businesses need to keep in mind the various data migration challenges that are likely to be encountered and look to upgrading systems or consolidating data centres to ensure better data management and data quality.
The ultimate goal of a successful data migration lies beyond just moving data; it has to preserve data integrity, usability, security and scalability in the new environment.
Let us dig in deeper, now.
Common data migration challenges and solutions
Data migration typically involves extracting data from a given source, transforming it as per the defined structure and matching it with the requirements of the target location and then loading it into the new environment. Effective planning is key in ensuring that this process is carried out as planned and is in line with the overall goals of data migration.
1. Loss of critical data:
Sometimes, format compatibilities can disrupt the transfer of essential files, possibly due to incompatibilities, schema mismatches, or network failures. This can cause the loss of important information, resulting in gaps and impacting business reporting and analytics. Differences in field types and sudden changes in validation rules can also lead to unusable, corrupt data post-transfer. Now, this can occur when data is migrated from an on-premises system to the cloud.
| Implement a clear-cut backup strategy and ensure periodic migration checks are carried out. Well-structured data mapping and pre-migration compatibility assessment can help with identifying potential issues. |
2. Downtime risks:
Downtime during data migration can disrupt core business operations, resulting in data gaps, frustrating employees, and the loss of valuable insights. Additionally, downtime can impact customer interactions, leading to reputational and financial losses.
| Systematic planning is a must, especially in e-commerce and businesses where downtime affects revenue directly. |
3. Data quality and security:
Inconsistent, duplicate, or corrupted data can cause significant hurdles during migration. Another common data migration challenge is security, as data during transfer is exposed to security vulnerabilities such as unauthorised access or data breaches. Most of the time, legacy data may have limited encryption, and this also increases security risks during the transfer.
| Clean and validate data first. Strong encryption and adherence to regulatory compliance need to be integrated in every stage. |
4. Complexities in data mapping:
Mapping data from the source to the target involves mapping all criteria, such as fields, structures, and data types. Now, if these do not have one-to-one correspondence, the data migration process can become challenging.
| Use a migration tool with built-in mapping attributes and conduct a mapping exercise beforehand. |
5. Integration:
Several organisations rely on integrated systems for efficient data sharing across platforms. Inadequate migration planning can result in integration breakdowns, where the new system fails to sync with existing applications or tools. This can lead to incomplete workflows, hindered data visibility, and inefficiencies in critical operations.
| Assess integration compatibility first, update all APIs and then adjust configurations. |
6. User training for change management and adoption
It is imperative to train resources before they adapt to a new data environment with different workflows and functionalities. This reduces the risk of human error and lowers the learning curve.
| Invest in comprehensive employee training programs to minimise disruptions. |
7. Increases in cost and timelines:
It is nearly impossible to stick to initial budgets and timelines; as unforeseen complexities such as additional testing needs or unexpected data compatibility issues usually arise. Having unrealistic expectations or projections can lead to rushed data migration, thereby compromising migration accuracy and causing data gaps.
| Keep a contingency plan ready, work with realistic budgets and timelines, and have clear communication. |
8: Optimisation and post-migration audit:
There is a high likelihood of data errors or performance issues just after you migrate the data; if left unaddressed, they may slow down business processes and adversely affect the performance and quality of the new system.
| A well-planned audit process, post-migration test runs and resolution of issues post data migration is mandatory. |
Businesses initiate the data migration process with various objectives, including upgrades and expansions, database migrations, or the integration of new data from other sources into their existing infrastructure. With a plan in place to handle data migration challenges, businesses can accelerate towards superior operational performance and sustainable scaling. Partnering with an experienced data migration consultant has become essential due to benefits like starting with a structured approach and a comprehensive assessment of the existing data landscape. An expert approach can help proactively catch data migration risks and accordingly design a systematic custom approach to the process. No matter the objective, there can be no more emphasis on data accessibility, security and most importantly, functionality at all times. Looking to future-proof your data migration efforts? Reach out to our team of experts right away!
