When asking industry experts, data integration and data migration are often used interchangeably. However, if you are looking at turning your data into insight, it is essential that you can differentiate between the two. While they both have data as a common denominator, the processes of data migration and data integration are quite different.
What is data integration?
Data integration is the collection and integration of electronic transactions, messages, and data from both internal and external systems or devices. The data moves to a new, separate data structure for cleansing, organizing, and analyzing it.
A business will typically use data integration when they want to get more insight from existing data, building a unified view of the organization. When sources are combined, it is far easier to get a holistic view of customers, stock, and transactions.
Data integration helps a business to scale by giving a complete view of customers. Only when you can see a holistic profile of your database will it be possible to target them in the right place at the right time. Customers demand a personalized service in the 21st-century, making data integration a critical part of your business strategy.
Businesses sometimes invest a considerable amount in data integration projects. McKinsey reports that most IT projects deliver less than 56% less value than expected. One of the biggest challenges is finding a solution that minimizes cost and optimizes resources to yield a positive ROI. Data integration tools help to automate the process instead of relying on in-house teams to do it manually.
Data integration projects need to have a definitive business need and serve a long-term purpose to be viable and generate a return on investment.
What is data migration?
Data migration involves the transfer of data. A transfer could be between different storage services, computer systems, or data formats. Whereas data integration involves collating information from disparate sources, data migration will move data that already exists from one place to another.
Data migration will usually be a requirement when moving to a new system, such as an upgrade. The objective is not to gain new insights, like with data integration, but rather for a safe transfer of data between systems.
It is very easy for data migration to go wrong without proper planning. A thorough plan needs to include:
- Data knowledge. Before starting the migration, you should thoroughly plan and prepare the existing dataset.
- Cleansing. Any issues with your data should be resolved prior to migration. A data quality analysis will point to any duplicates, incomplete records, and inaccuracies.
- Governance. The migration needs to have an audit trail to perform requisite integrity checks.
- Backups. All data should be backed up before starting a migration strategy to ensure no data is lost in the process.
There are two typical ways to conduct a data migration process. A “Big Bang” approach will transfer everything in a limited window, whereas a “Trickle” migration completes the process in phases. Testing is essential with either technique, throughout implementation and maintenance.
Data migration and data integration are different processes, but each serves the purpose of creating business value. Both migration and integration need careful planning if they are to be successful projects, requiring a deep understanding to develop a use case. Part of planning, data cleansing should be performed, contact StrategicDB to make sure your data is migration ready!