As companies increasingly rely on analytics to make critical business decisions, data is gradually becoming one of the main assets of an organization. In fact, its value translates into the monetary equivalent. That is why data migration is so important: a properly established data migration process can save the organization many hassles, including compromised security and expenses.
In this article, we will talk about the existing data migration types, outline the challenges of the data migration process, and list the best practices for migrating your data. Read on to learn more!
Defining data migration
In essence, migrating the data means moving it from one place to another. This implies changing the system of data ‘residence’ and, often, its format. Today the term refers to the transfer of data from on-premises into cloud environments.
Other cases for data migration are as follows:
- replacement or upgrade of outdated software,
- building a unified data pool for database centralization,
- adding infrastructure capacities,
- organizational restructuring requiring the consolidation of data, and
- enhancing incumbent applications with additional software solutions.
It is essential to distinguish between integration, replication, and migration of data. These terms are often confused, however, they refer to different processes. While data integration implies consolidating data from several internal and external sources in order to facilitate data governance, data replication means creating a copy of data while leaving the initial prototype intact.
As such, data replication is an integral part of data migration, however, these are separate procedures. After the data moves to a new location, all data replicas are erased from their former “place of residence” for good.
How does data migration work? Further, we will explore this subject in more detail. Let’s now focus on the different types of data migration.
Data migration types
All in all, there are several data migration types. However, companies often use a combination of them for their business and operational purposes.
Storage migration
Companies perform this type of data migration after replacing their legacy systems with new ones. It may refer to exporting the information from paper into the digital format, from one digital carrier onto another, or to cloud storage from the in-house company environment.
The benefits that organizations achieve through storage migration are quite significant, including, but not limited to, better data manageability, scalability and security. However, complete storage migration takes a lot of time.
Database migration
As the name implies, this kind of data shift refers to moving data into a different database. Databases are, in essence, not just data repositories: they also use different management systems (DBMS) providing a structure for information storage and organization.
There are two database migration subtypes: upgrading to a newer DBMS version and a complete change of DBMS vendor. The latter is way more complex. Moving data from outdated databases to newer solutions may also be challenging.
Application migration
This situation refers to changing a software vendor. A healthcare provider, for instance, may discontinue using one lab management solution and replace it with another. The data, though, will have to be moved into a different application ecosystem. The challenge often lies in converting it into a different format, used by the new software.
Datacenter migration
A datacenter is a hardware environment for data storage and computer processes. An enterprise datacenter is, literally, the aggregation of all server room equipment, including servers, processors, memory drives, etc. A company office may change its physical location and need to move its datacenter into a new place.
Alternatively, an organization may upgrade its existing hardware and shift the data into a new environment.
Business process migration
As the company expands and targets new objectives, business process migration may be in order. In this case, a company may need to move its databases and business-critical applications with their dependencies to new IT infrastructures.
Cloud shift
Cloud migration, i.e. complete or partial shift of enterprise operations to the public or private cloud environment offers organizations scalability, manageability, and budgeting benefits. Other kinds of data migration may be an integral part of a major cloud shift.
Depending on the scale of your organization, the data migration procedure may consume variable amounts of time, from several minutes to several months. There are also a number of challenges associated with data migration, as this procedure is by no means simple and requires careful preparation.
Data migration pitfalls
So what’s so challenging about data migration?
The data, in use by enterprise apps tends to be tightly interconnected with other data, application environments, and business processes. Ideally, data architecture, application design, and the logic of enterprise operations should correspond to each other.
In reality, though, this is rarely the case. Irreversible data loss or compromising its security and integrity are some of the top data migration challenges. The downtime expenses may also take a heavy toll on the company’s budget.
Based on the negative experiences of companies across industries, below are the top data migration challenges.
Outlining a data migration plan
The main mistake lies in taking data migration lightly. A good data migration plan, on the other hand, prevents the IT team from taking hasty steps and overlooking the important details of the complex project they are about to undertake.
Communicating with data stakeholders
By ‘stakeholders’ we mean literally anyone who may be interested in the data that you are about to migrate. Failing to warn them that you intend to transfer it, and update them about the current migration stages may bring complications.
Somewhere along the way, the need for this data may arise, and you may have to interrupt your migration procedure just to grant access to stakeholders.
Checking all the cross-object dependencies
In an organizational environment, data sets are typically connected with each other. Before data migration takes off, it is necessary to consider all of them, so that no dependent set of data gets omitted in the process.
With the special software and tools available today, including all of the dependencies, it shouldn’t be a problem. However, IT teams are routinely making the same mistakes in dealing with the dependency challenge.
Choosing proper data preparation software
Making sense of the innumerable data points manually is hardly possible, even if you run a relatively small firm. Data preparation software helps you decide which data is relevant for your needs, and which should be discarded as undeserving attention. Choosing the wrong software, however, may undermine your data migration efforts.
Setting up data governance policies
Proper data governance policies defining data access rights may considerably facilitate data migration. The main challenge lies in establishing these policies in advance, before the impending data migration. Usually, though, there is no concrete policy as to who may copy, create or modify data. This often leads to unforeseeable obstacles during the data migration process.
Access to relevant expertise
A lack of proficiency in data migration is yet another challenge. Companies performing data migration for the first time may be unaware of the obstacles and pitfalls. Successful data migration may sometimes require hiring a third-party company with working knowledge of how to do data migration to enhance the expertise of the in-house team.
Choosing the data migration strategy
You may have all it takes to carry out data migration, but the wrong methodology may interfere with your success. Choosing the optimal approach to data migration is one of the challenges that companies shouldn’t overlook.
Now that we’ve explored the challenges that data transfer may entail, let’s look at the data migration best practices.
Data migration best practices
Sadly, a vast percentage of businesses fail to conduct migrations that fully meet their expectations and standards. A lot of the best practices that we are listing below are the result of trial and error.
Here’s a checklist of what to keep in mind, if you want to carry out a seamless migration of your business-critical data.
Data replicas
Your files may get broken or lost in the process. Storing the back ups until the transfer is fulfilled will help you bring your files to their initial state, if necessary.
The state of data
To separate high-quality data from broken data, ask yourself the following questions:
- What data do you need to migrate?
- Where is it currently stored?
- What format will it assume after the shift?
- Is it currently up to data?
Your goal lies in picking a data migration strategy. Assessing the quality and the complexity of data will help you decide which method to choose.
Data standards
Setting up the standards for data will help you evaluate its quality. Data tends to change over time, and having clear standards to fall back on will help you successfully conduct both data migration and consolidation in the future.
Compliance and data governance
Setting up the rules for data governance is crucial, moreover, if you’re working with clients’ personal data, it may be subject to state regulation. For instance, if you’re dealing with your clients’ sensitive data, defining access rules is mandatory. The rules will also ensure data integrity. You may loosen your rules during the migration procedure, and return to stricter guidelines, after it is complete.
Data migration strategy
There are two main methods of data migration: moving everything in one big chunk (a.k.a. ‘big bang migration’), or splitting the process into steps (‘trickle migration’). The former will involve shutting down the entire system, whereas the latter takes longer, but helps organizations to avoid downtime.
Notifying data stakeholders
Notify anyone in your company who interacts with the data that you are about to move it, and inform them about the impending transfer. Communicate the steps of the data transfer to stakeholders as you proceed. Apart from mere ethics, this will help you minimize disruptions, in case anyone needs urgent access to the data.
Project ownership
Who bears direct responsibility for the data migration? Who will assess if its outcome is successful? Finally, who will evaluate data quality after the procedure has been completed? Define these roles before the shift takes off.
Data migration software
Most importantly, you need to decide on the optimal toolset for data validation, discovery and other critical tasks. Keep your organization’s specifics in mind when making your choice.
Risk management
Think nothing could possibly go wrong prior, during or after the transfer? Think again. The best practices involve listing the risks and having the emergency plan at hand before you start the migration.
Agile methodology
Modern development methodologies are equally applicable to data transfer. Use them to make the procedure more manageable and predictable.
Testing
Test as you go, not after you have moved all the data and deleted the backups. Run data migration testing after each logical project step. Further, we will lead you through the consequent data migration phases.
Key phases of data migration
An incremental approach makes even the most complex project doable. Data migration is no exception; below are seven data migration steps you should go through to ensure successful outcomes.
Step 1. Evaluate your data
Precise data evaluation will play a decisive part in choosing a data migration strategy. Your first step lies in identifying which data you will be migrating, where it resides, its core dependencies, current format, and whether it needs to be transferred into another format. As you go about this process you will notice possible risks.
Step 2. Define the scope
By now, you should be able to define the extent of data migration as well as the scale of your project, and estimate the project’s cost and timeline. Correct estimations will require in-depth analysis of both your initial system, and the new environment for your data.
An integral part of this phase is planning for potential downtime. This will help you choose the optimal time for data transfer activities. Notify data stakeholders after you’ve set up the schedule for migration.
Step 3. Create backups
Making backups is a necessary precaution you need to take before you commence the procedure of data migration. If anything goes wrong, backups will help bring your data back to its original state. Study the existing backup methods and choose the one that suits your needs best.
Step 4: Assess your resources
At this stage you will have to define whether you have the staff, expertise, time, and tools needed to successfully carry out your data migration. The questions you must ask yourself at this stage include
- Do I have enough in-house expertise?
- Does my team have enough resources to finalize the migration within the deadline?
- Which additional resources could come in handy?
This is also the time to reassess the features of the data migration software you have chosen for your project and determine if it really suits your needs.
Step 5: Perform the data migration
Both the original system and the system of destination must grant all the necessary permissions to perform the migration. Check if the data you are moving is of top-notch quality to avoid contaminating the new system.
Convert it into the necessary format and use the tools that you selected for data transfer. Supervise the procedure as it goes so that you could instantly intervene if anything goes wrong.
Step 6: Test
Check if there were any connection issues during the data transfer, then run the necessary testing procedures within the target system. The goal is to ensure that the data migration is done and that all the data is safely contained in its new location.
Step 7. Post-migration maintenance
Even at this stage you can’t be fully sure no data got corrupted or lost during the migration. Even after all the necessary tests, problems may still arise. Contact the full target system audit to detect and eliminate possible errors. One way or the other, wait until you have fully finished this phase before you delete back-ups.
Conclusion
At some point, every organization will be facing the necessity of data migration, whether due to the upcoming legacy system upgrade or because of the organizational mergers, restructuring, and acquisitions. Overlooking the importance of data migration may put at risk your organization’s most valuable assets and disrupt its operations.
Carefully estimating your project’s scope and complexity will help you define if you have all it takes to perform a seamless data shift, or whether you need to hire an external company.
Need a helping hand with your data migration project? Contact us now for a free consultation!
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