In this day and age where information grows and changes at the speed of the internet, data is touted as the new currency. Hence, data-related activities such as migration shouldn’t be taken lightly. It can serve as a stimulus for organizations to be more competitive and achieve strategic goals.
Stripped to its bare bones, data migration is a process of transferring data from one medium to another. The medium depends on what is to be installed or upgraded in the company’s environment. It can either be a storage system, application, database, or even data format. There’s also a growing trend of migration to the cloud from on-premise systems to take advantage of a scalable, secure, and cost-effective computing environment.
Debunking Myths Around Data Migration
While most organizations are familiar with data migration activities, a 2019 study by Gartner reported that more than 50% of data migration projects had surpassed timeline or budget, and in some ways had adversely impacted the business. This could be the reason why there’s a negative connotation linked with data migration. With the notion that it’s complex, resource-intensive, and cost-consuming, people just want to get it over with.
Most fail to see that the planning and the pre-migration stages are equally critical and that they should be accorded the right levels of effort and resources.
And with more terms thrown in like data conversion and data integration (sometimes used interchangeably), it’s even harder to get to know data migration ‘personally’.
Terminology and Definition
Let’s start by delineating the terms we often hear when it comes to data-related initiatives or projects.
This is a process of transforming data from the original format to a new one that conforms with the structures of the target system. It’s one of the earliest steps of migration process. Without data conversion, you run the risk of not being able to retrieve or read data off the new target system, leading to data loss and compromising the project outcomes.
Data integration, on the other hand, combines data of various types and formats from multiple sources. Examples of this include data warehouses and data lakes. It allows users to have a unified view of data with the ultimate objective of building big data analytics to gain business intelligence and insights.
This process usually comes after data migration for a company that has big data analytics systems.
How data migration fits in
In this scheme of things, data migration isn’t just about moving data from one medium to another. A data migration plan should precede it; prescribing the objectives, methodology, and tasks. It should comprise preparation steps like data audit to know the nature of data, data cleansing process, and encryption for data security, just to name a few. Only then can the actual migration proceed.
But the planning shouldn’t stop there. It should factor in post-migration steps to ‘tie loose ends’, so to speak. For example, putting in a governance framework to ensure the quality of new and existing data. Without this quality assurance, your data could be rendered outdated and inaccurate further down the road, thus defeating the whole purpose of data migration.
Complexity and Resource Intensity
Yes, your migration project could mutate into this over-budget, time-consuming, and highly-complex monster. But this becomes inevitable if prior planning and strategizing aren’t done, and especially so if you try to tackle the tasks all at once without dividing them into achievable milestones.
Take moving to a new house as an example. You’d want to plan first and divide the tasks into bite-sized chunks. Some pre-moving steps include sorting your stuff into boxes, labeling them, engaging professional movers, and allocating the budget. And with thoughtful planning, you know you’d need foam peanuts to cushion your boxed belongings, as an example.
What if no planning was done? Instead, you box your things away on the big day itself without categorizing and arranging them. Sure, your movers can wait for you, but that will incur extra cost.
What if you forgot the foam peanuts? Once you’ve arrived at your new house, your more fragile belongings might not even be in one piece!
And not to mention the arduous task of sifting through the jumbled-up boxes, sorting things out from the boxes, and placing them in the new area. Instead of relishing the fact that you have a new home, the unnecessary toil becomes a killjoy.
It’s easy to see how an unplanned, haphazard house-moving activity can get out-of-hand, over-budget, and resource-intensive. Wouldn’t an unplanned data migration be any different?
|House Move||Data Migration Project|
|Why do we need to plan?||Enable smooth, well-coordinated house-moving experience||Enable smooth delivery and completion of data migration that’s on time and within budget.|
|Examples of preparation steps||Packing things, labeling, engaging movers, budget allocation||Data audit, data cleansing, engaging technology providers, budget allocation
|Why can’t we do the steps in one go?||
|End game||Hassle-free move to a new home sweet home||Successful migration to a new environment with available, ready-to-use data|
With the terminology demystified and the components parsed into manageable parts, data migration isn’t as confusing and complicated as people made it out to be.
Importance of Data Migration
As alluded to before, the types of migration include technical scenarios like database migration, storage migration, or even data format update. This forms part of a bigger picture of replacing a legacy system, moving to a new application platform, shifting to the cloud, or upgrading a database.
Most people expect to reap technical benefits from these upgraded applications and services such as:
- Reduced storage and maintenance costs
- Minimized unplanned downtimes and interruptions
- Ability to scale system resources according to current requirements
No wonder they view data migration as a technical necessity.
With the Fourth Industrial Revolution upon us, organizations that want to stay relevant and competitive need to roll with the waves of digitalization and automation. This includes digitalizing their enterprise platforms. IDC has projected that by 2025, 3 out of every 4 business leaders will leverage digital platforms to adapt to the ever-changing markets and industries.
Again, data migration comes with the territory. But most don’t appreciate its importance in solidifying the success of a company’s digitalization journey.
Your migrated data sets serve as a building block in your new digital enterprise platform. With intelligent automation, real-time processing speed, simplified data models, and IoT connectedness, the underlying data is harnessed to provide the insights needed to move forward. These will fuel:
- Transformation of business processes to be more agile and responsive to current economic conditions
- Innovation capabilities to broaden revenue streams and open up new markets
- Improved customer interactions through usage of updated customer data
- Fact-based decision making through data analytics
- Collaboration and accountability across the organization through data accessibility and shareability
Essentially, they are key enablers to gain competitive advantages and achieve strategic goals for your company.
The Big Picture
Recognizing the vast potential and benefits, data migration should be in cohesion with your overall data strategy. This should be an incentive for you to come up with a comprehensive plan that considers both pre- and post-migration scenarios to ensure benefit realization beyond project completion.
It’s time to stop perceiving data migration as just another technical exercise. With the right mindset shift, planning, and execution that doesn’t veer off the master plan, data migration can open doors to infinite possibilities and opportunities for your organization.
Written by: Shigim Yusof