Five key considerations for successful data migration

Data migration is a critical process that involves far more than simply transferring data from one environment to another. It involves many factors, and has many implications, such as timing, cost, risk and regulatory compliance. Organisations have an ongoing imperative to establish correct data migration processes to effectively update core systems, centralise data management, and create platforms for reporting and analysis. Ensuring a smooth and secure data migration process requires careful consideration of data management practices. The main aim is to build a long-lasting solution that can work well in every environment.

Understand the importance of data migration and assess your risk profile

Data migration involves transferring select data sets from one place to another, whether that be between systems, solutions, or broader environments (locally or in the cloud). Following the recent cyber-attacks and privacy breaches within major organisations and the changing landscape associated with the risks of storing and maintaining data, it is crucial to assess your data needs and retain only what is necessary and carrying potential value.

With big data systems and file-based storage becoming more prolific in recent years, organisations have stored all available data without considering their current requirements or potential risks. It is essential to strike a balance between data retention and meeting data safety, regulatory, and privacy requirements. Additionally, identifying potential risks such as data loss, privacy breaches or cyber-attacks, and having the necessary security measures in place, is critical to protect your organisation from severe business disruptions.

Emphasise data governance

In addition to data migration, data governance is a crucial aspect in the management of data assets. It encompasses a set of policies, processes, and procedures that enable organisations to manage their data effectively. Strong data governance is required to achieve a centralised data repository, consistent data quality, accessibility, and usability. Benefits of data governance can be found in efficiency (e.g., increased data sharing), business value (improved decision-making leading to improved customer satisfaction) and risk mitigation (meeting regulatory requirements).

It is important to align your data policies with your business objectives and empower your employees with the necessary permissions to access and utilise data. Remember, these policies and processes need to be diligently followed and enforced by everyone in the organisation, which is why it’s imperative to have the right people, who understand their responsibilities when it comes to data governance, to oversee and manage data.

Leverage the right technology, solutions and environment

Implementing the right technology and creating suitable environments are crucial to complying with data governance policies. This includes storing the correct data (e.g. atomic, aggregated and derived data) in the right storage solution (e.g., file based storage, data marts or data warehouses) with the appropriate environments (e.g., on-premise, in the cloud or hybrid). By using suitable technologies and solutions, organisations can ensure smoother migrations and align with their data governance strategies more effectively. Moreover, each of these factors will play a critical role in setting up and ensuring a stable and systematic strategy for handling data across different systems, rather than a one-time data transfer.

Specific technologies needed will vary depending on the organisation’s size, data management needs, and industry. However, some commonly used technologies include:

Data management tools: To enable seamless integration and migration of data from different systems and applications. These tools also provide functionalities for data cleansing, data mapping and data transformation during the migration process.

Data quality tools: To assess, monitor and improve the quality of data within an organisation, helping to maintain reliable and trustworthy data.

Data security tools: Used to protect sensitive and confidential information, e.g., data masking, access controls and data encryption.

These technologies will need to be managed to ensure their effective implementation and ongoing maintenance within an organisation. This will include maintenance and upgrades, user support and training, performance monitoring and optimisation, and data governance. These practices will ensure organisations have properly governed data assets and rest assured their data is accurate and secure for the migration process.

Harness the power of artificial intelligence (AI)

AI plays a significant role in both data utilisation and data management. AI tools and techniques can greatly enhance the data migration process. By utilising AI in developing migration codes, classifying data efficiently, and predicting storage and usage requirements, organisations can optimise availability, archiving, and resource allocation during data migration. Some examples include:

Data quality assessment: AI can leverage machine learning algorithms to assess the quality of data during the migration phase, finding duplicates, missing values or inconsistencies.

Predictive analytics: AI can analyse historical data migration patterns to predict necessary resource requirements (e.g., storage capacity) required for a successful migration, helping organisations to allocate more resources if necessary.

Cost savings: AI-driven data migration can lead to less manual effort, increased efficiency, and minimisation of risk, resulting in a better return on investment (ROI).

Empowering organisations in the data era

Data migration and data governance are critical aspects of modern organisational operations. By carefully considering the five points outlined in this article, organisations can navigate the complexities of data migration while ensuring secure, efficient, and compliant data management. However, the objective here should not only be to move data from one location to another, but also to develop an enduring, cross-environmental solution that is instrumental in governing and facilitating data migration. Implementing the right technology and leveraging AI capabilities can enhance the data migration process, leading to improved data quality, data retention, efficiency, and cost savings. By bolstering a long-lasting, reliable system that extends beyond mere data transfer and serves as an effective bridge between diverse environments, organisations can successfully manage their data migration projects and unlock the full value of their data assets.

The views reflected in this article are the views of the author and do not necessarily reflect the views of the global EY organization or its member firms.