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Error handling

Process management1/5/2026Intermediate Level

Error handling is the process of anticipating, detecting, and resolving errors or exceptions that occur during the execution of software programs or data processes. It ensures systems remain stable and data integrity is maintained.

What is Error handling? (Definition)

Error handling is a process that manages mistakes or unexpected problems in a software system. It prevents system crashes and keeps data safe when something goes wrong. This process identifies where failures might happen and sets up ways to detect them. When an error occurs, the system follows a set plan to fix the issue or record the details. It also notifies the right people so they can address the problem. Good error handling ensures that users do not face broken pages or lost work.

Why Error handling is Important for E-commerce

Error handling is a process that manages mistakes within a software system. In e-commerce, this process keeps your store running smoothly when technical issues occur. If a product data import fails or a price update glitches, error handling catches the problem before it reaches the customer. Without these safeguards, shoppers might see wrong prices or broken checkout pages. This causes lost sales and damages your reputation. Effective error handling also saves time for your staff. It allows systems like WISEPIM to alert you about data issues immediately. You can then fix these problems before they impact your inventory sync or storefront accuracy.

Examples of Error handling

  • 1When a broken CSV file stops a product import, WISEPIM alerts the manager instead of crashing.
  • 2If an automated inventory update times out, the system tries again before flagging the product for a manual check.
  • 3When a customer tries to buy an out-of-stock item, the shop shows similar products instead of a generic error page.
  • 4If a sales channel cannot process a new product detail, the system blocks that specific update and records the error.
  • 5If a product image is missing during an export, the system uses a placeholder and notifies the content team.

How WISEPIM Helps

  • WISEPIM shows all import and export errors in one dashboard. This view helps you find validation failures and other issues to keep your data clean.
  • You can set rules that automatically find wrong or missing product data. This stops mistakes from reaching your webshop or marketplaces.
  • Create custom alerts for specific errors. These notifications tell your team immediately if a product update fails or an image is missing.
  • When WISEPIM finds an error, it starts a workflow to fix it. The system assigns tasks to the right people so they can correct and resubmit the data quickly.
  • Managing errors properly keeps your product information accurate and reliable. This reduces manual work and ensures your data stays consistent across every sales channel.

Common Mistakes with Error handling

  • Relying on user reports to find bugs instead of using tools that detect errors automatically.
  • Showing technical codes to users instead of giving clear instructions on how to fix the issue.
  • Storing error logs in different places, which makes it hard to find the main cause of a problem.
  • Failing to set up automatic alerts, which leads to slow responses during major system crashes.
  • Using different error rules in different parts of the software, which makes the system behave in unpredictable ways.

Tips for Error handling

  • Set up one central place to record all system errors and events. This makes it easier to track problems and find their causes.
  • Create clear error messages that tell users what went wrong. Offer a solution or tell them who to contact for help.
  • Use automated alerts to notify your team the moment a major error occurs. This helps people fix urgent issues right away.
  • Check your error logs often to find patterns or repeating bugs. Use this data to fix weak spots and improve how your system works.
  • Create a plan for different types of errors. Decide when the system should try again, use a backup option, or undo a data change.

Trends Surrounding Error handling

  • AI-driven predictive error detection: Utilizing machine learning to analyze system logs and patterns, predicting potential failures before they impact users.
  • Automated self-healing systems: Implementing logic that allows systems to automatically identify, diagnose, and resolve common errors without human intervention.
  • Enhanced observability platforms: Moving beyond basic logging to comprehensive observability, providing deeper insights into system health and facilitating faster root cause analysis.
  • Error handling in headless architectures: Increased complexity in distributed, decoupled systems requires sophisticated error handling across multiple APIs and microservices.

Tools for Error handling

  • WISEPIM: Essential for logging and managing errors related to product data imports, exports, channel synchronization, and data quality checks within a PIM environment.
  • Datadog / New Relic: Application Performance Monitoring (APM) tools that provide real-time error tracking, logging, and alerting across entire application stacks.
  • Sentry: A dedicated error monitoring and crash reporting platform that helps developers identify, triage, and resolve errors in real-time.
  • ELK Stack (Elasticsearch, Logstash, Kibana): An open-source suite for centralized logging, search, and visualization of error data from various sources.
  • PagerDuty / Opsgenie: Incident management platforms that integrate with monitoring tools to automate on-call schedules, alerts, and incident response workflows for critical errors.

Related Terms

data validationdata qualityproduct data syndicationdata stewardshipdata integritydata governancedata ingestiondata steward

Also Known As

Exception handlingFault toleranceError managementRobustness