Data Migration is the process of moving data from one place to another. In our previous blog, we discussed popular types, tools, and methods to transfer information. Today we are going to discover in detail how to execute the process of data migration. What are the challenges and difficulties faced during the activity, and what are some differences between data migration and other data-centric approaches?

How to Execute the Data Migration Process?

As briefly explained in our previous blog, the entire process of data migration is divided into 3 steps: Decide, Implement, and Check. Let’s explain them in detail:

1. Decide

This first step is difficult but very crucial. You will be responsible to access and filter your data from original sources. Along with this you will check the requirements for migration and test the approaches through which this migration is possible:

 

  • Data Filtering: First you will need to plan things beforehand. Planning will encompass the size, stability, and format of the data being migrated. You will have to audit on the basis of accuracy and data fields. You will filter the important and relevant chunks of data and clean the rest.
  • Design the Structure: After filtering the information, you have to design a structure. Every detail, for instance, processes, technical architecture, budget, and schedules will be listed in a hierarchy. 
  • Inform Stakeholders: A very important step in the data migration process is to inform stakeholders about your plan in hand. You should be in communication with all of your stakeholders. For example, what is the purpose of the project, what are its benefits, and what are the positive differences it will bring in the future? 
  • Create a Solution: Finally, you can start to codify a formal data migration. It’s time to transform and shift the data into a new storage system. 
  • Check That Solution: Check your process at least 3 times before going forward. This is also called a testing phase. Recheck multiple times after completing your code multiple times before going toward the implementation phase. 

2. Implement

In the second step to data migration, you will implement things practically. This might be frustrating at the beginning. Because stakeholders will be reluctant during this movement. But if you have comprehensively checked your solution then you can go forward with confidence. 

3. Check

To ensure your migration goes in the same direction as you planned, you should confirm things at every step. Whether it’s planning, development, or testing. Check that the data was transferred smoothly on the basis of accuracy, and data loss. 

Last but not least, you shall close the process wisely. Shut down everything on competition and close the connection of the legacy systems that backed up your data from its sources. This will benefit you with cost savings and resource efficiencies. 

Is Data Migration Difficult?

The short answer is “Yes”. But Why? This is because of the term data gravity. It happens when the data volumes become parallel in growth to its number of usage. In simple terms, it is the most noticeable aspect of huge datasets that shows its potential to attract smaller databases.

As time passes data migration is connecting with cloud infrastructures. To move applications and information to more reliable landscapes you need to open the information to some extent. A simple solution to make things easier is to start solving the complexities of data and applications.

Besides this, another problem is that every application misinterprets the concept of data management. This happens when application logic gets mixed with it. To solve this complexity, data migration is leveraged so management of this information gets some awareness and priority.  

What are the Challenges Faced during Data Migration?

Despite data migration having some emphasis on technology over the past many years, it also has some downsides. Below we have compiled some challenges that organizations faced during this journey:

Not Informing Stakeholders

Not informing stakeholders can sink your project. No matter the progress, quality, and size of the migration, if you fail to inform your stakeholders about the project you fail at everything. Data is something that can be important, confidential, and influential for someone. 

Before going forward your first job is to inform your stakeholders on anyone in charge before implementation. 

Communication Gap

After informing your project to stakeholders, make sure to keep them updated about your performance. This would be possible through efficient reporting without delays. You would be responsible for maintaining efficient records and keeping everything on track. 

Smooth communication always becomes a challenge if not maintained respectively. 

Accountability

Responsibility is another big challenge in data migration. It should be obvious who will report to whom. It would be wise to decide who will be responsible for creating, editing, accepting, or deleting the information from the database.

Decision Making

Many organizations invest in the right decision-making. They hire experts from different parts of the world to create a think tank to plan things in the right direction. A lot of time is given to brainstorming sessions just for the sake of successful data migration. 

Despite such a strategy, sessions don’t always guarantee success. However, having a concrete data migration strategy can save you from sudden losses during the journey. 

Skills

Lack of skills will absolutely become a problem. Despite the size of data being migrated, tons of records, important information will be at stake if not handled by a professional. When we say professional we mean an expert with excellent references to keep the process going smoothly. 

Absence of Data Preparation Tools

Automation has always been believed to bring quality and quickness two times better than humans. The same expectation goes for data migration tools. By investing in a first-class application solution selecting the best provider will be a challenge. 

Unreliable Approach

Research is something that takes your planning in the right direction. You would be responsible for some research to be sure that the data movement process has worked positively for other firms like yours. 

Difference Between Data Migration and Other Contemporary Approaches

Data migration is most of the time confused with other identical terms. For instance data conversion and data integration. These terms are always misconceived with data migration. So let’s clear this misconception:

Data Migration & Data Conversion

Data migration is the method through which we move data from one location, format, or platform to another. It includes many processes like data profiling, filtering, verification, and quality approval. 

On the contrary, data conversion is only limited to format. It is the process of changing information from one format to some other format that can be used in a different database, application, and storage system. Moreover, it is required to transfer the information from a legacy app to an upgraded format of the same app. 

Data Migration & Data Integration

Data integration is the process of combining data from various sources to form one unit. This methodology helps businesses to make better decisions and grow faster with a comprehensive and perfect dataset. 

Unlike data migration, It is a unified view of all the information. Thus integrating the data from different sources is significant for reporting and analytics. 

Conclusion

Hopefully, now you will be super clear about the data migration process. We also cleared the challenges encountered during this process and its differences from other data-centric activities. 

Want to learn more?

Visit Integrated IT Solutions about key aspects of data migration and how it can transform your business.