American tennis player Roger Crawford once said, “Being challenged in life is inevitable. Being defeated is optional.” During IT projects, challenges and barriers to success are inescapable. However, they are not necessarily insurmountable; being aware of such obstacles early enables you to overcome them.
In the world of data integration, a few challenges will crop up along the way. This article describes what those barriers to success are and how you can prevail to achieve the results you want.
Challenge 1: Defining Data Integration
One of the biggest challenges of data integration is defining it. Data integration is often used interchangeably with business integration and system integration, but they are different.
REMEDI defines data integration as “the collection and integration of electronic transactions, messages, and data from internal and external systems and devices to a separate data structure for purposes of cleansing, organizing, and analyzing the joined data.” Data integration takes place in a data warehouse and requires specialized software to host large data repositories from internal and external sources. The software extracts, amalgamates, and then presents the information in a unified form during this process. When you use the right term to define the process, you will be one step closer to getting the results you want.
Challenge 2: Data in Heterogeneous Forms
Another major problem that crops up during the data integration process is information in heterogeneous forms. Legacy systems store data in different forms; however, a single data integration platform cannot handle heterogeneity. It must all be in the same form for analysis.
Overcoming this challenge involves an awareness of heterogeneous data formats from the outset. Evaluate your information formats early in the project. Next, a developer must convert the information into a format that the data integration platform can handle. That way, you can analyze your data.
Challenge 3: Extracting Value from Data
A common complaint about data integration is that it's difficult to extract value from your data once it has been integrated with a variety of other sources. It is not just that there is a great deal of information out there (there is, and it keeps growing every day thanks to sensors, mobile devices, and social media). Your analytics tool must be able to connect to the data integration platform for that data to be of any use to you.
This is a problem that can be easily solved at the beginning of the data process if you remember what analytics tools “talk” to your data integration platform (and vice versa). By making the right technology choices, you avoid a situation where your integrated data is rendered useless.
Data integration can pose multiple challenges during the implementation process if you do not approach it the right way. Successful data integration requires knowledge and thorough planning. To learn more about the right way to handle data integration, contact us today.