Is Your Data Integration Technology Outdated?
Spring is a good time to get rid of the old stuff and check out something new. This might as well be the time to upgrade your data integration tools. How can you learn if your data integration solution is outdated and should be replaced by something more productive? May be it just needs a little tuning? Here are the main check points to see if your solution’s performance still fits the industry standards.
Data transformation schemas deal with both data structure and content. If data mappings are not as well-organized as possible, then a single transformation may take twice as long. Mapping problems can cause small delays that add up. The solution to the transformation issue is to make sure that data maps are written as efficiently as possible. You can compare your data integration solution to the similar ones to understand if the data transformation runs with the required speed.
Business rules processing are specific rules for the data that has to be validated. Too many rules can suspend your data integration processes. You have to make sure that the amount of rules in you data integration system is optimal, meaning that there are not too many of them running at the same time.
Network bandwidth and traffic—in many cases the performance is hindered not by the data integration tool itself, but by the size of the network you use. To avoid this issue, you need calculate the predicted performance under various loads and make sure you use the fastest network available for the data integration needs.
Data integration solution reminds a car: it can run but become slow if it is not properly tuned and taken care of. As we become more dependent upon the data integration technology, our ability to understand and optimize the performance issues will make a substantial difference.