Data migration helps to improve the performance and competitiveness of an organisation. It involves consolidating data where the legacy systems are deployed or replaced, and the main purpose is to improve the performance of the business and provide competitive advantages.
Data storage degrades with time, and changes should be made to enhance its value for improving integration to new applications. Data migration helps to eliminate wasteful data, reconcile databases for better use, and improve the security of valuable data.
How to Migrate Data?
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Organisations must analyse the requirements, resources, and other factors to move information. Unplanned migration can lead to underestimation of the project, leading to issues such as redoing the process repeatedly.
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Companies should estimate the skills and processes required before starting it. It should involve maintenance and management.
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It involves selecting a new system to fit new requirements, new supplies, businesses or opportunities where the information is moved in different file formats, architectures, environments, servers, etc.
Role of Cloud
The process may involve a shift to cloud-based systems, consolidations, modernising, and upgrading applications. Cloud is becoming one of the leading deployment options for data shifting. The reliance on the cloud system has increased significantly since 2014 as it improved the connectivity and scalability of the applications. Cloud has the benefit that it helps to manage infrastructure and security and promotes scalability.
Virtualisation
Methods such as virtualising can be adopted to manage information in secondary servers. It can even help to consolidate IT to improve the infrastructure ecosystem, which can be transferred easily anytime and modified as per the future requirements of the business. The virtual environment is easy to shift. On the other hand, the cloud is highly complex and requires proper implementation planning.
Strategies
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The strategies companies adopt to migrate may involve big bang plans or trickle, where the big bang requires the company to shut down operations for a short duration to shift data from one system to another. During this time, everyday business activities cannot be carried out, whereas, in a trickle, data is shifted parallel with real-time transactions.
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Future changes are integrated through remigration. In such systems, the movement of information continues during many stages, while, in a big bang, the data is moved from one to another in one step, where it may not require future migrations.
Defining Metadata and Content
The process involves defining information identity – the keywords or codes identifying the data source's location and characteristics (length, character, etc.).
Testing
Testing involves reviewing the source data and code amendment, and retesting is needed in most cases of data migration. Poor business plans can lead to significant repetitions of work, extra costs, and time, leading to expenses more than the allocated budget.
Poor data migration planning can lead to remedial data cleansing. For example, if the data is found to be wrong at the end of acceptance testing, it may take months for the organisation to fix all the moved data.
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