Data Migration

What is Data Migration? – How to Implement it?

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Data migration refers to the procedure of movement of data from a specific location to a new one for bringing an improvement in the system. It is effective in the preparation, selection, and transformation of data for transferring the same from one storage system to the other. Data migration is useful to the business organization in raising the technological and optimization advancements. Thus, enterprises opt for data migration for the movement of their existing infrastructure to different cloud-based applications and storage.

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Data migration offers immense opportunities to the business for increasing their growth, surging the agility and determining the priorities of the business. It also plays a vital role in decreasing the capital expenses. They help to transfer the applications to an innovative and improved environment. 

Steps to implement data migration

There is a wide assortment of companies which have the wrong notion that data migration is an easy task. However, the truth is that there is much more to the process other than the movement of the content from a specific system to the other. Here is a list of the steps, you need to implement to ensure a cost-effective and successful data migration.

Development of strategy

The data migration contributes to being a highly strategic procedure. Before the implementation of data migration, you should ensure to solidify the objectives of the business which will be facilitated by the migration process. 

According to the starting point of the data migration, you can find a wide array of vendors which will offer assistance in the process. However, you need to keep in mind that these vendors can handle only a specific part of the process of data migration such as the movement of the content. It is not possible for them to extract business intelligence from them.

You need to make a careful evaluation of the different capabilities, required by the business. As you are done with the concept stage and have found the right solution, you need to let your team confer a boost to the process. To ensure a smooth and successful data migration, make sure that the business and team teams are aware of the requirements of the migration project. 

You need to gather all the key stakeholders on board as well as coordinate with them to ensure the top quality of data migration.

Analysis and assessment

Now that you have developed the strategy for data migration, the next step involves the assessing of the content. In this stage, you need to find answers to specific aspects such as the format of the current content, the amount of content, you are planning to migrate, the attributes of the file, the total percentage of duplicate content, how much of the data is absolute, redundant or trivial or how old the files are.

Thus, you need to combine the workflows and share drives which involve the migration of the content. With the use of a plethora of filters, you can figure out how the content is stored and how it is possible to organize the same. You can also opt for paper-based content to make sure that no crucial documentation is being missed out.


In this stage of migration, you need to digitalize the remaining part of the paper-based content. With the incorporation of paper content before choosing the next stage of the migration process, you will be able to go forward and save ample time.

As the content gets digitized, you need to remove the ROT content as well as pre-process the remaining part of the data. Other possibilities of the step are inclusive of increasing metadata for ensuring better searchability, compression of content, and conversion of the same into PDF or the universal format. It is not feasible to accomplish all the steps manually. Hence, it is recommended to opt for the services of a technology firm, with ample experience in the industry.

Extraction and classification

In this phase, you need to sort the content into different categories in which you are planning to migrate. Now that you have ensured that the content is usable and of high quality, and it is not an unknown group of files anymore, you can begin to route the same in the right bucket. Thus, it is possible to categorize the content according to the age, file type or other criteria.

In this step, you also need to complete advanced extraction of data. It is possible to leverage the information like the categorization of the various entities in the legal documents, seeking supplier name from the invoices for the creation of different data rules which will be useful in determining that the content is sorted via the migration procedure.

Staging and validation

This phase involves the reviewing of how the process is going on. Take your own time for assessing the rules of the data migration. Make sure that they are working in a specific way in which they are supported too. Here, you need to map out different exceptions to the routing of data. Though the majority of the procedure is automated, you need to check out the information to make sure that you will not encounter any hassles in the future.


By following the above-mentioned steps, you now have a well organized and clean data set to deal with. Now, you can transfer the data from one content system to the other one. At this stage, it is possible to get access to the content completely. It is also possible to leverage the content for different organizational requirements like the fuelling of the big data analytics, streamlining of the workflows, tightening up of the compliance measures and improvement of the data security.

Bottom Line

To ensure that the process of data migration is successful, make sure to follow the above-mentioned steps. Data migration ensures the comprehensive integration of data. It reduces storage and media costs. Thus, it helps in bringing an improvement in the ROI of the business.

TowardAnalytic is a site for data science enthusiasts. It contains articles, info-graphics, and projects that help people understand what data science is and how to use it. It is designed to be an easy-to-use introduction to the field of data science for beginners, with enough depth for experts.

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