4 Key Terms Used When Developing a Salesforce Test Data Migration Plan

Every once in a while, you have to change your business’ systems. Migrating from the old system to a newer one is always exciting because you will be moving to a better performing system. However, this migration poses a great risk to the data that you have acquired over the years. Loss of data is a major cause for worry for many business owners. For this reason, you have to ensure that you set in place the best data migration strategy.

[easy-tweet tweet=”Migrating from the old system to a newer one is always exciting” hashtags=”data, systems”]

Data migration is not as easy as plugging in a flash drive or a memory card to your computer and transferring to another one. It is a time-consuming process and one that will require serious planning. It is nonetheless one of the most beneficial tasks for all businesses. You will be upgrading to better data management practices and better-performing systems. In order to conduct the whole process, you will need the services of a data migration expert and your database administrator’s assistance. You also need to understand what is meant by the following terms.

Legacy data

Legacy data is simply the data that you want to move to another system. It goes without saying that the source of this data is the legacy system. It includes the information that is currently recorded in your storage system. This could be anything from scanned images and paper documents to database records, text files, and spreadsheets. All these formats of data can be shifted to another system.


This is a tool that is used to move the data from the legacy system to the new system. Flosum is one of the best data migration tools that you will find in the market today. You can access it at http://www.flosum.com/salesforce-data-migrator/ and it will help your data migration process by simplifying it. This migrator works with just about all methods that you might want to apply in the data migration process.

Data migration

This is the process of exporting the legacy data to the target system through the data migrator. It can be done manually or be automated. The specific method that you decide to use for the data migration process is totally dependent on the systems that you will be using as well as the nature and state of the data that will be migrated.

Data cleansing

Cleansing of data must be done before you begin the migration process. It is all about the preparation of the legacy data for the migration to the new system. This is done because there is a disparity between the architecture of the legacy system and the target system. Often, the legacy data will not meet the criteria that are set by the target system. Data cleansing, therefore, manipulates the legacy data so that it will meet the requirements of the new system.

[easy-tweet tweet=”Cleansing of data must be done before you begin the migration process” hashtags=”bigdata, tech, cloud”]

The bottom line here is that if you understand the basics of data migration, you will have a really easy time finishing the whole job. These above-mentioned terms are among the foundational features of every data migration project. A good comprehension of them will help a lot as you plan the data migration project.

+ posts


Related articles

Don’t lose sight of SAP on Cloud operational excellence

Digital transformation projects can often become complex with twists and turns, which can lead organisations to focus solely on the migration itself.

Need to reduce software TCO? Focus on people

Investing in software is undoubtedly important for enterprises to stay ahead. However, the process is rarely a simple task for CIOs and IT leaders.

The future of cloud and edge optimisation

As more enterprises use multi-cloud and hybrid infrastructures, the danger of cost overruns and loss of control increases.

Here is how to stage a public cloud migration

As the relationships between CSPs and cloud providers are deepening, CSPs need to develop a clear strategy on how they add value to customer relationships.

The future of work is collaborative

As hybrid work models continue to gain traction, businesses will need to start implementing collaborative tools and processes to meet the needs and expectations of the upcoming workforce, seamlessly integrating them into existing workflows to enhance productivity and performance. Innovations in technology, including AI and machine learning, mean that organisations are in a better position than ever to shape the collaborative future of work – and with the right support in place, they can ensure that these digital tools continue to bring out the best in their workforce for years to come.


Please enter your comment!
Please enter your name here

Subscribe to our Newsletter