The basic definition for data integration is "combining data from different sources and providing unified view of data to users to support decision making".
When we have a quick look why data integration is getting more important?
- Technology is taking place in all processes within an enterprise and this requires data integration from transactional and operational systems to decision support systems
- Everyday new technologies, which give new opportunities to enterprises, are being developed. This requires data integration between current systems and new systems
- Data is everywhere, in every type and produced by everyone. Unstructured data use is growing and importance of Big Data is increasing which also require new technologies in data integration field
- Data production and consumption cycle is getting shorter and real-time data requirements are increasing which also requires developments in the field
In AberdeenGroup's report, "Ever Harder and Faster: Managing the New Demands of Data Integration", we can see the increase in unstructured data use. I do not have any reference for more up-to-date data but I guess increase in external unstructured data use is higher. Thanks to developments in Big Data, it is possible now to analyze external data from internet and especially from social media to support decision making process. (e.g. to manage marketing campaign)
In the same report, it is stated that "use of integration tools maximize the types and quantities of data that can be integrated and delivered to business managers".
Data integration tools provide data quality and validation controls and make data transformation easy. If number of systems and data volume is small, coding might seem as an easy and applicable solution. However, when data requirements are increased, new data sources are added to the system, coding will get more complicated and performance will degrade. Data integration tools make it easy to expand data sources and to adopt new data requirements. Other than these, tools provide other benefits like, real-time data process, tracebility (also by business users), automation ...etc.
There are different vendors providing tools or packages for data integration. At this point, it is good to have a look at Gartner's Magic Quadrant for Data Integration Tools.
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| Gartner's Magic Quadrant for Data Integration Tools |
(http://www.gartner.com/technology/reprints.do?id=1-1HBEFSF&ct=130717&st=sb)
You can find detailed strengths and cautions analysis of vendors in the report. Whether you are searching for a data integration tool or you are new to the field and trying to understand what should be expected from a data integration tool, this report will help you.
You can find detailed strengths and cautions analysis of vendors in the report. Whether you are searching for a data integration tool or you are new to the field and trying to understand what should be expected from a data integration tool, this report will help you.
