Error handling is crucial for successful data integration, but error handling isn’t easy, which is why it’s often overlooked.

Data integration between applications has become an essential part of any business workflow, but data integration is complex. The ongoing challenge is how does an organization close data gaps? Duplicate data and data errors are common, and having clean data is critical to any integration project. Without clean data, your business is unable to confidently and quickly make decisions based on the information it collects and produces. One thing that always holds true when it comes to business data is that if you have useless data going into your business, you will inevitably have garbage information going into your business.

Error handling is crucial for successful data integration, but error handling isn’t easy, which is why it’s often overlooked. Understanding the source of data errors and implementing corrective actions is complicated and can be daunting. An integration platform that can simplify data error handling is invaluable to developers and end users.

Types of Data Integration Errors

The more data an organization has to manage, the higher the risk of data integration errors. Data discrepancies should be quickly identified and resolved; therefore, it is essential for companies to be able to locate integration errors easily. Here are some of the most common mistakes:

Featured resource: Why successful onboarding is a team sport [Read Now]

  • Data Errors – The data does not match the schema defined for the input or output.
  • Process Errors – This is usually the failure of a data stream during execution.
  • Authentication – Authentication errors occur when the credentials provided to perform an integration are not valid.
  • Business Validation Errors – An error occurs when a data request is rejected because it violates business rules.
  • System Threshold Errors – This type of error can have multiple causes, such as exceeding the number of allowed API calls.
  • System Availability Errors – This is a common error resulting in incomplete integration due to a link or system failure.

The growing adoption of software-as-a-service (SaaS) platforms contributes to the number of integration errors. As more SaaS solutions are adopted, integration errors need to be identified, documented, and reported. An error handling system should be in place to troubleshoot SaaS integration issues.

It’s usually non-technical staff who have a problem with data integration. If the data is not formatted correctly or there are other issues, they can try to fix the problem themselves. When that doesn’t work, they get an error message. Without proper error handling protocols, it’s hard to know who can fix the problem. The error message can be escalated to IT, the integration development team, or someone else. At the same time, emailing back and forth to resolve the issue creates delays. Even when the problem is fixed, the user who had the problem in the first place may not know that the problem has been fixed, which means a greater loss of productivity.

See also: Backend Data Integration Challenges in the Cloud Era

Handling integration errors

One way to minimize integration errors is to stop using custom coded integrations. When developers create a custom integration, they often become complacent and don’t care about errors. But, data errors will inevitably occur. In such cases, the system generates a general error alert, which makes troubleshooting difficult.

Adopting an error handling system standardizes error handling. A Hybrid Integration Platform (HIP) offers greater transparency and provides a comprehensive error handling process. Real-time problem resolution also minimizes data integrity issues and downstream failures and promotes better system reliability and productivity.

Adopting a HIP to connect data assets and applications simplifies error handling, providing alerts on data flow, process errors, and system failures. It provides a graphical representation of the actions needed to correct data errors. A HIP also provides specific instructions for citizen developers and data management teams, simplifying error handling. This level of transparency eliminates the need to sift through lines of code and visual streams to locate a particular error.

With a HIP, non-technical users can manage the operations portal to see if data is flowing properly between systems. Being able to identify the problem early allows for faster resolution. Also, it no longer causes delays with “error tennis” which involves emails being exchanged between frontline users and IT support to resolve the issue.

See also: Cloud integration: APIs to the rescue

Shorten resolution time

There’s an old adage among enterprise developers that 50% of the integration work is doing the integration and 50% is fixing the implementation and fixing any unforeseen errors. As hybrid integration platforms continue to evolve, CTOs should look for integration solutions that include a full suite of error handling features to reduce troubleshooting time.

Giving non-technical users greater visibility into integration errors means less work for everyone involved. Business decision makers should consider choosing a HIP with comprehensive error handling capabilities to promote collaborative error resolution. Allowing users to monitor and, to some extent, manage data integration makes sharing data between environments simpler, more efficient, and less error-prone.

The role of any integration platform is not just to support a wide range of integration options. It also makes data integration faster, easier and more reliable. The sooner you can integrate different data sources, the sooner you can convert that data into actionable insights.

Featured resource: Why successful onboarding is a team sport [Read Now]