Automation in Data Migration

Digital and data transformation is no longer a discretionary investment. While the push for transformation is more pervasive is some industries, all companies wishing to remain competitive in the digital economy are undertaking several data-led transformation initiatives. The spend on digital transformation, according to the latest IDC report, is expected to reach US$4tn by 2027

Where data-led digital transformation is involved, data migration is a necessary step to ensure that data in legacy systems are not lost and the company continues to extract value from data built up over the years – whether for operational agility or for competitive advantage.

A sizable portion of the growth in digital transformation is being driven by productivity improvements brought about by automation and AI. This article explores the productivity improvements seen specifically in data migration – a necessary and traditionally labour-intensive and time-consuming activity in digital transformation projects. More importantly, it provides an overview of the role of automation in driving efficiency and cost-effectiveness during data migration.

The need for data migration

Data migration, fundamentally, is the process of moving data between storage systems or computing environments. It is necessary for reasons such as system upgrades, corporate mergers, compliance requirements and infrastructure evolution. The data migration journey, however, is fraught with challenges: ensuring data integrity, reducing system downtime and cutover time, overcoming compatibility issues and managing budgetary constraints. Irrespective of its nature, the data migration process involves a few key structured stages: source data extraction, mapping of source to target, cleansing, transformation and loading, with each stage being followed by validation and testing. Typically, one or more pilots are conducted to ensure that the migration addresses the data requirements of the target system and data quality KPIs.

Cost implications and the role of automation

Data migration operations are often associated with significant expenditure, driven by factors such as labour intensity, protracted timelines, technical complexities and the critical need for risk management. Automation therefore emerges as an important lever in mitigating these costs, enhancing speed and/or improving time to market. It streamlines manual tasks, expedites migration processes, enhances data accuracy and provides scalability and adaptability. The most profound impacts of automation within the ambit of data migration are witnessed in areas such as data cleansing and preparation, data mapping, data validation and testing, as well as monitoring and reporting.

Implementing automation: tactical examples and methodologies

The following diagram illustrates the primary areas where automation holds potential for data migration purposes, outlining how these dimensions might become evident in a migration project. It demonstrates the often unused potential of automation in the data migration process.

Various tools available on the market are designed to automate the data cleansing process – a crucial step in ensuring data quality and integrity. Rule-based mass updates and migration criteria make for fast and automated cleansing.

Sophisticated tools dedicated to the task of data mapping help streamline the complex process of aligning data fields between different systems, thereby enhancing overall efficiency. Script-based approaches utilising AI enable data value mapping to be improved.

Automated testing frameworks exist that play a critical role in verifying that the migrated data adhere to operational standards and perform effectively in the new environment. Data validation solutions conduct audit-proof and automated validations for full data sets and make fast adoptions possible.

Advanced platforms exist that are capable of creating real-time monitoring dashboards. These dashboards are instrumental in providing ongoing insights into the migration process and help in making timely and informed decisions.

To ensure the operational reliability and efficiency of automation solutions, a comprehensive and methodical approach is essential for the effective deployment of these tools.

Business use case for automation

Not all data migrations are candidates for automation, and a simple, ‘back-of-the-envelope’ calculation can tell you if the effort (hours to build/cost of tool, etc.) is worth the value (faster deployment, improved data quality, etc.) that automation brings. Typically, a few factors play a significant role in making a favourable case for the use of automation:

Migration complexity – This can take many different forms. It may be due to lack of documentation of the data model/data lineage in legacy systems, especially when multiple databases or nested tables are involved. Complexity can be project-related, where the migration needs to balance business availability, resource availability or release cycles, or requires co-ordination across multiple teams/time zones. Whatever the form of complexity is, involving automation forces the migration team to carry out a deeper analysis and configure the rules in alignment with data owners, thereby allowing for a more controlled, phased, scalable and repeatable migration process.
Business criticality of the data – If the data to be migrated are business critical, automation makes the process less error-prone and more predictable.
Frequency – If the data migration is not a one-off activity or if a trickle data migration strategy is used, automation will result in consistency, speed and security.

A high-level approach to identify, build/buy and monitor an automation for data migration is noted below:

Implications: the future of data migration

The integration of automation into data migration is a productivity-enhancing initiative in today’s digital transformation landscape. Far from being a mere trend, it is a necessity for organisations striving for operational efficiency, cost-effectiveness and data integrity, as evidenced by experiences from our various client engagements. As we look to the future, the path of data migration is inextricably linked to the effective use of automation tools. Embracing this shift is not just an operational imperative but a necessity for organisations aiming to maintain a competitive edge and agility in a technology-driven marketplace.

In short, the data migration landscape is undergoing a significant transformation that is propelled by the advent of automation. This shift is not just about operational enhancement but also about redefining the tactical framework within which businesses conduct data migrations. Automation in data migration is a pivotal element in the digital transformation journey, enabling organisations to harness data more effectively and drive cost-efficiency.

If you are searching for the right tools and use cases for automating your data migration and making it more efficient, please get in touch with us. We’ll be happy to provide you with our expertise, help you choose the right vendor for your data migration automation use case and guide you through a successful data migration.