In today’s day and age, data migration is something most growing businesses eventually face. Unfortunately, very few executives are adequately prepared for how to handle it. Are you confident that your business can take on data migration and survive to tell about it?
Overcoming Key Data Migration Challenges
A study from Bloor Research shows that the failure rate for data migration projects is an astonishing 38 percent. In other words, more than one out of every three data migration projects experiences a hiccup, which can prevent businesses from performing normal business activities, hurt their reputation, and potentially costs thousands of dollars when it’s all said and done.
The big question is why? Why is data migration so difficult in today’s business climate? According to NetApp, the answer is data gravity.
Data gravity is essentially a metaphor used to describe how data attracts other data as it grows; how this data is integrated into an organization; and how the data becomes customized over a period of time.
When it comes to moving data from physical storage and servers to cloud infrastructures, the gravity becomes even more intense. This often leads executives to make big mistakes and oversights, such as these:
1. Lack of Strategy
A data migration is a highly strategic process. Before the implementation phase, be sure to solidify the business objectives that your migration project will facilitate, Adlib Software advises. Do you need to consolidate your systems following a merger or acquisition, or has your organization simply been struggling with a surplus of content?
If you don’t wrap your mind around specific strategic goals, your migration will be misguided and sloppy. It’s possible that you’ll still end up where you want to go, but it’s highly unlikely. A documented strategy will serve you well.
The two most common types of migration are big bang migrations and trickle migrations. Though some organizations may use different titles, they operate as follows:
- With big bang migrations, everything happens in a single defined window. There’s system downtime in which the data is extracted from the source system, processed, and then loaded onto the target system. The processing is then switched over to the new environment. The speed and efficiency of this approach are beneficial. The disadvantage is the amount of downtime that’s required to complete the migration.
- Trickle migration is a more incremental approach. As opposed to attempting a full migration in one fell swoop, the old and new systems are run parallel to each other “ migrating the data in phases. The benefit is zero downtime. The disadvantage is that it takes more time to complete (leaving the migration susceptible to a greater risk of error).
As you determine your approach to data migration, you’ll have to account for the various complexities that your organization faces. Explore as many different strategies as you can and don’t be afraid to try something new.
2. Poor Knowledge of Data Source
You need to prep your data before migrating it. Otherwise, you’re going to end up with a huge mess on your hands. Set up meetings with all of the appropriate department heads in your organization and make sure everyone is on the same page.
It’s imperative that you’re aware of any issues that exist with your data. This includes duplicates, misspellings, erroneous data, missing information, and formatting issues. Unless you deal with these issues up front, the new system is going to have a hard time handling your migration requests.
3. Poor Budgeting
According to one study conducted by Bloor Research, the average budget for a data migration project is $875,000. But despite this, just 62 percent of projects are brought in on time and on budget. The average migration has an overrun of a whopping $268,000.
Don’t underestimate the cost of data migration. A lot of executives do this out of wishful thinking “ hoping they can find some savings for their company “ but it’s a suicidal pursuit. Data migration can be expensive, and you need to make sure you’ve carved out enough space in the budget to see it through.
Accurate budgeting is about identifying potential hidden costs and accounting for them as much as possible. The primary cost driver is time. The longer it takes to migrate, the more expensive it gets. Other risks include the opportunity cost, data corruption, data loss, and shadow IT (which emerges when understaffed IT teams are forced to deal with infrastructure problems by looking outside the business).
4. Inflexibility
We started this section by discussing the importance of having a strategy. But no matter how good your strategy is, things will change along the way. Issues will arise, challenges will emerge, and you’ll see things that you didn’t know were there. If you continue to stick to the plan and refuse to change, you’ll compromise the entire process.
Flexibility is a must with data migration. You have to be willing to optimize your approach, shift your timeline, and tweak the plan so that the transition is seamless and successful. As a leader, your charge is to lead your business through challenges “ not around them. Data migration is a big challenge, but it has to be addressed in a head-on manner.
Take Data Migration Seriously
When it’s all said and done, data migration needs to be taken more seriously than it often is. This isn’t something you can afford to play around with. There should be no testing of strategies or trial and error. You need to have a concrete plan that you follow through on. In doing so, you’ll avoid many of these challenges and counteract the force of data gravity.