Every organization depends on large amounts of data these days to manage its day-to-day operations. There will be times when you need to convert or move data depending on whether the data is moving from one system or several databases into one. Although the terms “database migration” or ” database conversion ” are often interchangeable, they are two distinct processes that are crucial to an organization’s software implementation.
What Is Data Conversion?
Database conversion is the process of removing data from an inactive database and converting it to a more useful format. Then, it propagates it to a new, better-suited instance. The format of the data after conversion is determined by the target database. Video or music files must be converted to a format compatible with your phone. An MKV file must be converted into an MP4 file to be used on your mobile device.
Database conversion should aim to preserve the integrity of all data. If the target source format is the same, it may not be necessary to convert data when moving data between databases. If the data format of the source database is not consistent with the receiving instance, then a database conversion may be necessary to properly maintain, analyze and read the data in the target.
Data Conversion Process
Although every database conversion project is different, there are some common steps that all conversions must follow.
- Analyze both the source and target databases.
- Create a plan that is based on the requirements of the project and the needs of the end-user.
- You should test the conversion at least three times and then quality-check the results.
- You can implement the plan by converting or transforming the data to the format required by the target database.
- The final results are quality-checked.
Issues Related to Data Conversion
Understanding the source and new format is key to the complexity of database conversions. This knowledge is essential to avoid data corruption or loss of data integrity. Duplicate data may also need to be combined; obsolete data may need to go before conversion, or incorrect data may require manual correction.
What Is Data Migration?
Database conversion refers to the transformation of data into another format, but database migration is the act of moving data from one format, system, or source to another. Data migration requires that the target source perform quality assurance processes such as cleansing, profiling, validation, and validation of data.
Database migration is required by most organizations when they are upgrading their systems or using cloud solutions. There are three main types of a database migration: storage, cloud, and application. The process of migrating data from old databases to more modern versions that allow access to a newer system is called storage migration. Cloud migration is the process of moving data from one cloud instance or data center to another cloud. Migration is the process of moving an entire application to another location or moving existing data to a new version.
Data Migration Process
Data migration involves reviewing the current state, mapping data to identify inconsistencies and discrepancies, then transferring data to the new database. Finally, testing is done to verify that all data has been successfully migrated.
Issues Related to Data Migration
Although it may appear simple at first, database migration is quite complicated. It is important that the new system has matching fields for existing data. Otherwise, the data may be lost during the migration process. As part of a database conversion, the process to ensure that data sets are correctly mapped is usually performed before any migration. It is important to plan properly before performing a database conversion in order to reduce the likelihood of problems.
Outsourcing Data Conversion and Migration
Outsourcing data conversion or migration is a good option to avoid data loss or destruction. Despite their technical abilities, few IT staff are qualified to handle data conversion and migration projects. An experienced provider can help your company’s database upgrade process go more smoothly. You can have peace of mind about security and performance with a quality deployment model, especially if you have data that is not well-organized, unusable, or out-of-date.