Top 12 Best Practices for Data Migration Projects to Keep a Watch in 2018
Data migration projects is a sheer headache for any business.
It is data migration projects that takes a toll on your budget and on the schedule.
However, data migration is something necessary to stay updated with the technological advancements and industry standards. You need to test, analyse and clean up both on-site data and cloud data.
The new rules, responsibilities and practices that your employee has to comply is also a challenge. Along with that is the discovery of untouched data transformation rules due to lack of business ownership which might lead to inaccurate data in the legacy systems.
Data migration just seems easier, but it is not. Often project managers view it as a part of a large underlying project and schedules data migration near the end of the project rather than in the beginning. Therefore, leaving an analysis of data migration to the last leads to fatal failures.
Around 70% to 80% data migration projects fails to meet the expectations.
Why Data Migration Projects Fail?
The call for data migration best practices is due to several reasons. Causes that led to the failure in data migration projects includes –
- Failure in copy process
- Server might crash
- Target storage device might crash and might become unreachable
- A minor or major data center issue occurs
- Bad data might get corrupted from the beginning
Top 12 Data Migration Best Practices You Need to Keep a Watch in 2018
Let us look inside the loop and find out what are the best practices for data migration in 2018.
- Calculate how complex is the data migration and determine its scope
The most important practice that guarantees successful data migration projects in 2018 is the evaluation of the resources and how they store the data or how complex the data is. The complex data strings and data classification system may influence the direction of your organization to a great extent, so put an eye on it.
- Its high time to de-duplicate the data
The best practices for data migration tells that you can overcome all data problems by extracting, transforming, sanitizing and de-duplicating the data.
- Maintaining the data standards
Before your business move forward after the data evaluation, make sure you come across a comprehensive set of data standards in place. As data is do integral to any business, since it is an ever-changing, establish a bunch of new rules and standards while conducting data migration projects to ensure successful use of data in the upcoming future.
- Underlining the current business rules
Underline the business rules so you can apply the use of data. These rules comply and must be compatible with the business and validation guidelines. It is not only for the current data migration projects, but also for the future policy requirements.
- Determining the governance responsibilities
Helps to establish the governance of a new data system by figuring out who will take the final say – the one who manages the information or the one who is responsible for supporting data quality, access and usage. The entire company feels affected by the data migration. So you need to be careful when you choose team members and managers to handle the important tasks or technologies.
- Have some strict data migration policies
To move the data, you need to enforce the data migration policies. Say for examples, you need to enable data migration at overnight hours when the network usage is low and would not interfere with your data migration project.
- You need to keep a tap on the quality assessments
Data migration in 2018 is much more than moving data from one point to another. Before you transfer any data from one system to another, you must first assure the high level of quality, once the new database goes live to the current users. The data quality should involve the removal of duplicate contents and files that is not relevant for the current or future business.
- Assess the risk migration
You need to gather and assess the risk related to your data migration projects. You need to be a little straightforward while you set the rules and standard quotients. Analyze how and where the organization data will come to use and who will use it and how is it going to change the future.
- Spot the right tool
After you have done your homework, it is time to recognize the right tool for creating a new data environment. Remember that tools are only good when they support your infrastructure and you should never see it as a solution to all your problems. The proper tool, helps you to customize the rules and align with your organization and recommended by experts.
- Analyzing the risk management
Risk management is one of the integral part of the data management process. It should be an integral component of the migration process. Make sure that all data is acceptable for any potential audits and all information must comply with government and as per company or industry based standards.
- Change in the management
This might be the most important metric for a successful data migration in 2018. Managing the change within in the organization requires careful consideration of users, customers, vendors and partners who will take part in a new system. This will ensure a successful transition for everyone who’s in and keep everyone on board for the long haul.
- Testing, validating and auditing
You need to test the migrated data and make sure they are perfect and accurate. Without proper testing and validating, you cannot find confidence in its integrity. You need to audit the document process at each stage and preserve a clear audit trail of which data runs into which one.
What’s Your Take?
These are some of the best practices for data migration that will rock your 2018. It will reduce the pain of managing complex data migration projects and give it the best chance to succeed.
If you come up with any more additional best practice, share it with us in the comment box below. We’ll be glad to know them.
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