Data, as much as it is a lifeblood of our business, can also be Achilles Heel for various reasons, sometimes reasons best known to none!
If you are in the Business Data Integration stream, the complexity only multiplies exponentially. When you are selling an integration product, you are by default understood as flawless integrator of data regardless of any factors. But we are not living in an ideal world are we?
Solving Data Quality Issues
More often than not the data received and described, is never as accurate, never as complete or never as consistent as it is required to be. The result of this would be data flow not being as smooth as intended. When the result isn’t the best the actions and conclusions based on it will not be the best as well, eventually leading to a dissatisfied customer. Some of the common issues encountered as a result of poor quality of data,
- Data duplication – The key reason for this to happen is that systems do not have proper keys (primary or external ids) i.e. the keys that tie applications.
- Application Crashes – This could happen for many reasons ranging from machine or servers to amount of data transfered.
- Half data being moved – reasons include limitation of data transfered or system governance limits to errors in mapping or data quality or validations
- Performance lag – reasons could be in-adequate resources applied to the integration software to network bandwidth allocated to the integration.
- No synchronization – reasons include in-correct credentials, data mapping errors or data validation issues.
As with any product, with evolving times, comes in more automation targeting performance enhancements and more sophistication, meaning lesser room to ensure data quality. Integration process without accurate, consistent data is as good as integration without the data and eventually business without customers. So it is absolutely necessary to strike the right balance between the two.
Over a period of time we have followed best practices to ensure a smooth integration as any amount of data profiling, data management, data cleansing can ensure at best what can be described as a half solution and not a complete one. Hence we believe in incorporating Customer intelligence into the product and this is being done by gathering key facts about the customer, their nature of business and their data usage and management, a step that not only gives an edge over competition but more importantly also ensures a step ahead in having a satisfied customer.
