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Data Integration vs. Data Migration; Know the Difference
Data is considered to be a vital asset for different small scale firms as well as large business organizations. Data migration and data integration primarily involve data. Data migration services involves the transfer of data between storage types, computers, and file formats. Data integration, on the other hand, combines the data present in various sources for offering a view to the user.
What is data migration actually
Data migration refers to the process of moving data between different storage devices or computers. It involves a wide array of migrations like the application, database, storage, and business process migration. A wide array of organizations opts for data migration owing to different reasons. Data migration is done for the maintenance of the server, upgrade of the storage devices. Data migration is also useful for the replacement of data storage devices. In addition to this, data migration is conducted for merging the website, recovery of the disaster, and relocation of the data center.
However, business firms require effective and efficient planning as well as validation techniques for reducing the impact of this transfer of data on performance and compatibility. Automated data migration is helpful to reduce human error. Apart from this, it plays a vital role in reducing the application time. It also brings enhancement in the migration speed. Furthermore, documentation of data migration is useful in reducing future risks and expenses. Once the data migration is over, the business organizations require validating the statistics for monitoring the accuracy of data. In addition to this, data cleansing is useful in enhancing data quality with the removal of duplicated and unnecessary data.
What is data integration actually
Data integration refers to a process in which data from multiple sources are combined for offering a view to the user. Data integration can occur in a wide array of situations like the scientific and commercial applications. For instance, two firms may feel the urge to merge the databases. Similarly, you may need to combine the research results in the single storage.
With the improvement of functional units and business processed, the amount of data needs to be increased. Such type of large quantities of data is referred to as big data. With data integration, it is possible to share the big data among several systems. Data integration let the external users and external members of the team share the data.
The data warehouse of business is regarded as the most popular implementation of data integration. The data warehouse is useful to the businesses in performing different analyses based on data, present in the data warehouse. This is impossible to do with the aid of the data in the source system. It is because the source system does not consist of the corresponding data. Though the data is not named identically, there are regarded as various entities.
Data integration refers to a term which covers a wide array of distinct sub-areas like data migration, data warehousing, master data management, information integration, and enterprise application. Data integration is essentially the blend of business and technical processes which are used for combining various data from different disparate sources for turning the same into valuable business insight.
This technique gives support to the analytical process of data by the combination, alignment, and presence of data store to the end-user. It is known to be conducted in the data warehouse with the aid of specialized integration software. Transform, extract, load or ETL happens to be the most common type of data integration. However, other techniques of data integration are inclusive of virtualization and replicable which are effective in the transfer of the needle in specific scenarios.
Difference Between Data Integration and Data Migration
Data migration contributes to being a process in which data is moved between the data architecture, format, storage type, and enterprise system. The data integration primarily involves the collection of data from a wide array of sources outside the business firm for analysis. Data migration, on the other hand, indicates the movement of data which is already stored in various systems internally. Business firms migrate the data type with the merging to another environment or implementation of a new system. A wide array of automated scripts or set of specific programs which transfer the data automatically are used for conducting the data migration process.
Here is a list of a few of the differences between data migration and data integration:
Data integration is recognized to be the technique to combine the data, present in various sources. It offers a unified view of the user. Data migration, on the other hand, is considered to be the process of extracting, preparing, selecting and transforming the data and moving it permanently from one system to the other. This explains the difference between data migration and data integration.
Data integration involves the combination of data from multiple disparate sources which are stored with the aid of different technologies. Data migration, on the other hand, primarily involves the preparation, selection, transformation, and extraction of data.
Data integration is useful in replacing or upgrading the present system. On the other hand, data migration is known to combine the applications of two business firms. It is also useful in consolidating the applications in a specific firm. This is another worth mentioning difference between data integration and data migration.
Data migration and data integration are completely two different processes which are related to data, of a business firm. The primary difference between data migration and data integration is that data integration is known to combine the data, present in various sources for conferring a view to the user. Data migration, on the other hand, is useful in moving the data between the storage types, computers, or file formats.
Data migration and data integration are known to vary in several ways. Integration of data from different sources is a must for the data analytics because the business firms look forward to offering a single unified view of data to the users. On the other hand, data migration happens to be a process where new storage mediums or systems come into play and the business may need to move all the existing records to the new environment. 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.
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