Data Migration is typically most neglected title of the project that embraces movement from old system to new system. Data Migration projects tend to be time-consuming and costly, often requiring extensive application downtime. It is important, expensive and difficult but it is unavoidable.
At primary level it affects several key IT infrastructure components. For example, it’s often an expected step when companies acquire new hardware, deploy new applications, or upgrade existing applications. It plays a successful role in storage strategy, process redesign, especially when the movement and placement of data affect process performance.
It is a head-most point to accomplish data migration at right time at right place which requires team efforts. Group the team that involves database administrators, application people and members who know testing and quality assurance to justify quality and conformity staff to approve documents.
- Select the Data to Migrate:
First decide what data you need to migrate, where it is placed and what is the form of it. Know about the sources of data you need to shift. When you know where to locate the data and understand how it’s stored, you can determine which elements from each of your sources you’ll require.
- Abstract and Convert the Data:
Improve the quality of your data by identifying and removing the errors or any issues. This might include standardizing formats or enforcing naming conventions. Now convert your data. At which point you’ll need to determine how to get the old data into the new format. Fortunately, ETL and other automated tools can handle most of this process. ETL tools (Extract, Transform, and Load) are very well suited for the task of migrating data from one database to another.
- Move the Data Consistently:
Once you’ve determined how to transform your data, you begin the largely manual process of actually transforming it. Automated tools are available that can also help confirm a consistent process. Store the backup copy of original data.
- Evaluate the Migrated Data:
Test the migrated data to check that it’s an accurate sketch of the original data, and it’s in the familiar format. Without any testing and evaluation you can’t be confident about its functionality.
- Analyze the Process Thoroughly:
Once you have established the functionality of data, you will need to prove it. What you had done in each stage of migration process should be documented. Create a traceable audit trail of who did what to which data and when.
To succeed, data migrations must be given the attention they deserve, rather than simply being considered part of a larger underlying project. The ultimate aim should be to improve corporate performance and deliver competitive advantage.
Read More Data migration Steps.