Data Integration: Performance Issues
It’s been written so much about challenges of data integration initiatives, about all those mistakes and issues that organizations face starting from the preparatory level, so when, at last data integration at an enterprise starts working everybody sighs happily.
However, they miss at list one thing to worry about. It’s performance. What’s wrong with performance, you say. Well, according to David Linthicum, computing and application integration expert, there are two main data integration performance issues:
- The first occurs due to the organic data growth. Being a common issue for both real-time and batch data integration model, it results in the system failing to get and deliver the needed data in time, providing undesirable latencies.
The second issue is a result of bad data integration architecture. This happens when core data integration performance requirements have been poorly formulated, or wrongly understood. The mistake leads to wrong technology or approach selection.
What’s so dramatic about it? Well, let’s think. Why someone starts data integration initiative? Let’s say, to have a better look and access to data needed for business. If this data doesn’t appear in target systems when it needed by the business process, the goal of data integration initiative was not achieved.
So, plan data integration architecture properly and keep an eye on performance.