Data Integration Service

Last Updated: February 10, 2017

Definition - What does Data Integration Service mean?

Data integration service is the employment of a group of services that comply with service-oriented architecture. Data integration service can perform in an N -> 0 latency time period. At the same time, it offers a powerful set of transformation processes for meeting an array of business imperatives. The advantages of employing data integration as an enterprise service include reduced time for marketing, a reduction in total cost of ownership (TCO), and a solution to the obsolete and expensive data-integration patterns presently available in corporate businesses.

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Techopedia explains Data Integration Service

A data integration product should be platform independent. It should also have the capacity to integrate data regardless of the following:

Required frequency
Communication protocol
Business rules needed for intricate integration patterns

There are primarily three types of products that stem from the data integration space:

Extract Transformation and Load (ETL): These products are built to move large data volumes while offering the capability to carry out effective transformations. They are often found in a batch process algorithm. This is due to the availability of data volumes and the frequently used transformations like summation, aggregation, sorts and multi-table joins.
Enterprise Application Integration Products (EAI): These are often known as brokers or messaging software. These are designed in such a way that they move a smaller amount of data with amplified frequency patterns.
Enterprise Data Replication (EDR): These products present information when data sets are modified or changed. These are delta-processing or change-data capture products. They often work on either a triggering or log-scraping mechanism. Also, they offer a pointer to the last extraction point for tracking the data that has been processed.