An Overview of Data Integration Tools and Software

With modern organizations creating large volumes of data as part of their routine operations, there is a growing need for data integration to deal with complex data center environments with multiple different systems. This data has to be understood and analyzed in the aggregate and not in isolation. Data integration at its core is the technique and technology for providing a unified and consistent view of data across an organization.

What can data integration software and tools do for a business enterprise?

•It can process unstructured data from social media, web pages, email.

•Specific software can carry out syntactic and semantic checks to ensure that the data is following business rules and policies.

•Cutting-edge data integration tools can process data from a wide range of sources like enterprise applications, mainframes, proprietary databases, spreadsheets, and more.

•Remove duplication and incorrectly or improperly formatted data and provides support for metadata

All these goals can be achieved through various data integration software and the efficiency of each is dependent on the different approaches prevalent in an organization. The main technologies for data integration are Extract, Transform, Load (ETL), Enterprise Application Integration (EAI), and Enterprise Information Integration (EII).

Of the three, ETL is highly optimized for data integration and migration of large volumes of data, thereby being a very useful tool for data analytics and decision making in any enterprise. It is a process where large volumes of required data are extracted from various databases and converted into a common format. This data is then cleaned and loaded into the specialized reporting database called a data warehouse, and made available for standard reporting purposes.  

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