Data migration helps to improve the performance and competitiveness of an organization. It involves consolidation of 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 database for better use and improves security of valuable data.
How to migrate data?
To move information, organizations need to analyse the requirements, resources and other factors. Unplanned migration can lead to underestimation of the project, leading to issues such as redoing the process repeatedly.
Companies should estimate the skills and processes required before starting it. It should involve maintenance and management.
It involves selection of 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 shift to cloud based systems, consolidations, modernizing and upgrading applications. Cloud is becoming one of the leading deployment options for data shifting where the reliance on the cloud system increased significantly since 2014 as it improved connectively and scalability of the applications. Cloud has the benefit that it helps to manage infrastructure, security and promotes scalability.
Methods such as virtualizing can be adopted to manage information in secondary servers. It can even help to consolidate IT to improve infrastructure ecosystem, which can be transferred easily anytime and modified as per the future requirements of the business. Virtual environment is easy to shift, on the other hand, cloud is highly complex and requires proper planning to implement.
The strategies adopted by companies to migrate may involve big bang plans or trickle, where big bang requires the company to shut down operations for a short duration to shift data from one system to other and during this time, everyday business activities cannot be carried out, whereas, in trickle, data is shifted parallel with real time transactions. Future changes are integrated through remigration. In such systems, the movement of information continues during a number of stages, while, in 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 which can identify the location of the data source and characteristics (length, character, etc.).
Testing involves review of the source data and code amendment, and retesting is needed in most case of data migration. Poor business plans can lead to significant number of repetition of work, extra costs and time, leading to expense more than allocated budget.
Poor data migration planing can lead to remedial data cleansing. In case the data is found to be wrong at the end during acceptance testing, it may take months for the organization to fix all the data that is moved.
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