Transfer of data from one location to the other is not an easy task. However, when it comes to data migration, hundreds and thousands of data are migrated across the system. Such kind of data transfer is complicated. With complexity, arise issues at times. It may lead to the delay of transfer of lengthy data during migration, thereby giving you a major headache.
For avoiding any such issues during the migration, here we have mentioned the three crucial challenges, you may face during data migration and tips to resolve them.
Source Data Complexity: 1st challenge
As the complicated data migration service involves the transfer of a sheer volume of records, there are chances that you might run into different challenges with the source data. It is not like moving any information to the content management systems. Here, you might need to conduct configuration and analysis for working via the source data complexity. Here is a list of the elements which may increase the complexity as well as few techniques; you can opt for, to solve them:
Data transformation
Each mainframe is known to store the data in a specific way. In case the data storage format you choose is outdated, you may require transforming the data, as you are willing to store the same in any modern database such as SQL server or oracle.
Codified fields
Storage of claim numbers of thirty to forty digits in a single field should be a common practice in the latest content management system. However, in case you are planning to move to a different system, it is recommended to break the specific kinds of codified fields so that they can be used at ease. As you do the same, you will be able to view the relevant information such as member identifier, sequence number; data has parsed out quickly, instead of looking at a specific lengthy number, and decode it in your head.
Normalization of data
In case you are using the same old content management system for a long time, there are high chances that your firm have similar pieces of these data stored in a plethora of various places. You need to adopt the process of data normalization in which you have to find each place in which every single piece of data is stored. Here, you need to make sure that data is stored in the right place only once. Thus, there are reduced chances of errors during the migration of data.
Corruption or loss of data: 2nd challenge
It is obvious that corruption or loss of data can be a serious issue and can lead to a disaster in your data migration project. There are high chances that your business firm might have to go through potential loss if there is loss or corruption of even a single data. Here is a list of two techniques which will be useful to you in avoiding any such issues during the migration of data, thereby reducing the chances of data corruption or data loss
Reconciling the accounts during migration and testing
Before the starting of the data migration process, you need to keep a count of the total records that are brought in along with the total count of records that should be present in the target system. You need to remember that it is not a must that the total count of data in the source and the total count of data in the target system has to be the same always. In case you find that the output has not matched the expected number, you need to research to find out the reasons.
Use of specific tools for the validation of the migrated data
As you transfer the data from one specific location to the other, you have to make sure that the documents which have been migrated in the specific system match with your expectations. A wide array of data migration tools are available for the purpose. You need to make the wise use of these tools to find out whether there is the exact number of characters in every claim number field. A wide array of commercial utilities and services are present which can help check the veracity of every field of the data.
Thorough testing as well as validation of data: 3rd challenge
When it comes to the content management system, the total count of data involved in the data migration process is high. Thus, the cost of failure is too high. Here is a list of few of the data testing and validation processes which will be useful in testing as well as validating the data thoroughly:
Consider the data events which can affect the quality of data
In case your content management system has undergone a glitch in any year, make sure to take note of the same. In such cases, it is a prerequisite to test every piece of data separately for ensuring that the data is of good quality. Though it may consume some time, it plays a vital role in removing the chances of any hassle at a later off stage.
Testing the larger volume of data for ensuring quality
It is recommended to draw ten to twenty percent of the data at least for ensuring that it covers a wide area. In case you are transferring data for multiple years, it is commended to pull almost five percent from the last year apart from the profile sample data.
Test early and often
It is recommended to start testing as soon as you get the chance of doing it, even if you get it to do with a specific subset of the code and configuration. You should continue to run the tests during the whole data migration process. You should ensure that testing is a consistent procedure.
Data migration is a crucial process. Hence, you need to think about the challenges and address them quickly to avoid any hassles later on. If you’re making any drastic changes or improvements at your product or software, doesn’t it make sense to go with a company like Indium Software - Leading QA Solution Provider.
Thanks and Regards,
Bavana Princy