Data Integration: Best Practices You Need to Keep in Mind

by Tech Geekk writer

The thing about data is that on its own, it makes no sense and thus, is unable to serve any purpose for the entity seeking to leverage it. However, find the right way to connect it and voila! You instantly get the bigger picture and can glean meaningful insights from it. That’s the thing about data — it is typically sourced from a variety of sources and needs to be appropriately organized and then connected to the appropriate data before it can start to make sense. Also, as the sources for data continue to grow, data integration helps bring together disparate pieces of information in a consistent format to allow businesses to gain access to data-driven insights.

Given its many benefits, it is understandable that companies undertake data integration projects for the sake of their business. Unfortunately, reports show that the gains achieved are far short of expectations — in a vast majority of cases. It is typically ascribed to some challenges and the lack of implementing best practices in the project. In this article, we’ll list the leading best practices for data integration to help you ensure that you can derive the best value and ROI from it.

Figure out the requirements: It is a big no-no to set out on a data integration project without figuring out the business’ requirements. It is essential because the needs will help you determine the most relevant approach to tend to the qualifications above. Furthermore, it will also allow you to make sure that the vendor’s proposition is in sync with your needs.
Incremental data updates are the way to go: Incremental data updates will help you accelerate the integration process. What happens is that whenever data sets are updated, instead of replacing the entire data, only the new information is added to the pipeline. We won’t deny that incremental data updates are complex and take much time to implement, but trust us when we say that it is worth every bit of it.
Widespread collaboration: One can’t deny that data integration is anything but simple. Moreover, this is why it is essential to pool in resources and continually work together, not merely within a team, but across different groups as well since all digital processes are largely interconnected with various facets of a business.
Pick the right platform: No matter if you want to execute data integration using Talend, a highly recommended name in the market, or any other such tool, be sure that you have carefully thought the decision through and factored in the business’ needs, your goals, expectations, requisite skill set, and more. Oh, and let’s not forget the total cost of ownership along with ownership costs also play a crucial role in this decision.

So, long story short, data integration may seem daunting at first, but as long as you keep these best practices in mind and pick a tool that will truly complement and serve your requirements and goals, you will have a seamless journey.