How to handle data integration errors

By Beate Thomsen, Co-founder & Product Design - April 02, 2024

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Ensuring transparency in data transfers is a critical challenge in data integration, notably between CRM and ERP systems. 

This transparency is vital for effectively managing errors—a common pitfall in integration planning. Experience in building custom interfaces between systems highlights the importance of anticipating and preparing for potential disruptions.

When something goes wrong—and let's be honest, it's more of a "when" than an "if"—you might find that you have planned for the system to transfer data but not to handle a data or connection error.

Sure, your systems might throw you a bone with a vague error message, but figuring out what went wrong and how to fix it? That's all on you. And getting everything back in sync is no small feat.

This becomes a whole different ballgame when you're not just syncing a couple of fields but transferring heaps of important customer or order information. You're in for quite the challenge without your system automatically picking up the slack.

FINDING OUT WHERE DATA INTEGRATION ERROR COMES FROM

The first step in any data integration error handling is to determine what your data integration errors are due to. The most typical errors come from poor data connections. They could also come from bad or missing data in the source system, causing validation errors in the target system.

Sometimes, errors are due to a new system update in the source or target systems. It is actually very rare that an error is caused by the integrating system itself.

error-handling-with-rapidi

Error handling with a data integration platform

Organisations are using a growing number of systems to collect precious customer data. CRM, SCM, ERP, and data warehousing systems gather and store data. As the data amount increases, we refer to it as Big Data. This could result in data silos.

Businesses need to combine data from different sources to obtain high data quality and have a unified view of their customer data. Consolidating data from disparate sources or data warehouses requires data integration tools.

From that moment on, we recommend businesses to consider data storage, data access, data virtualization, and data transfer. Data integration systems use different data transfer methods. 

For example, some use the "ETL" procedure that extracts, transforms and loads data to transfer it.

Many businesses are using data integration platforms such as the Rapidi data integration solution to solve their data integration needs. This gives them the transparency and control they need to handle errors in data transfers.

Data integration platforms provide the required data mappings and migrations between standard fields. This allows you to minimise the number of data errors.

Data Integration Handbook 
A data integration platform like Rapidi provides a log that contains information about all transfers, whether successful or not. Many systems simply display an error message in the data integration system when an error occurs. This does not provide you with all the information you need

While it is crucial to get informed about the problem when it occurs, knowing how to solve the problem is even more critical. Receiving information about the additional action needed to prevent new errors of the same type is vital.

Rapidi provides all the necessary information to ensure your system is always running. It helps you identify errors, diagnose them, solve them, and prevent them from reoccurring.

HOW TO EASE THE ERROR-HANDLING PROCESS

There are different ways to facilitate the handling of data integration errors.

Rapidi provides an automated error escalation and handling system. When an error occurs, it automatically sends an email to the integration administrator(s). The message contains the exact error message from the system that created it and a direct link to the data transfer that contains the error.

This makes it easy to investigate a problem. When you detect a data transfer error, you can simply correct the data in the source system. It is then automatically transferred the next time a data transfer for this table is scheduled. 

Alternatively, you can rerun the transfer manually.

Some integration solutions display their own error messages. These are created by the data integration and not by the actual source or target system. 

It is a simpler way to handle error handling from a programming perspective. However, it does not provide the end-user with precise information to solve the problem. The preferred method should be utilizing error messages from the source and target systems.

When you have a setup with direct batch interfaces between two systems, you will often not receive any messages if the batch is not running. Therefore, you might assume that everything is running fine. However, you can never be sure that this is the case. That’s why this type of system makes it difficult to have reliable, error-free data.

When you select a data integration tool, one of the most important parts is not knowing whether it can offer real-time data transfers. Most systems offer real-time transfers. Most often, companies do not even need real-time integration.

But more importantly, you need to ensure that the solution monitors the schedules and sends you notifications if they don’t run for a certain amount of time. Then, you will never have to worry about solving data integration errors again.

FREQUENTLY ASKED QUESTIONS

What are common challenges in the integration process?

Common challenges in the integration process include ensuring seamless integration, managing the risk of errors, and dealing with poor-quality data from external sources. These challenges can significantly impact customer experience and business operations if not appropriately addressed.

How can integration issues affect customer satisfaction?

Integration issues can lead to disruptions in real-time data processing, resulting in delays or inaccuracies that negatively affect customer experience. Poorly integrated systems can compromise the quality of customer service and, ultimately, customer satisfaction.

Why is careful planning essential for successful data integration?

Careful planning is essential to address common data integration challenges effectively. It helps identify potential integration issues early, develop a comprehensive integration strategy, and ensure that the integration aligns with business objectives for a seamless experience.

How do integration errors impact business decisions?

Integration errors can lead to poor quality or incomplete data, affecting the accuracy of business decisions. Without comprehensive insights and quality checks, businesses risk making decisions that could adversely affect their operations and profitability.

Can traditional data integration methods meet today’s business requirements?

Traditional data integration methods often struggle to meet today’s business requirements for real-time data processing, timely insights, and the ability to handle large volumes of data from various sources. Advanced tools and proactive planning are necessary for achieving these objectives.

What are the key steps to mitigate the risk of errors in data integration?

Key steps to mitigate the risk include implementing comprehensive quality checks, using advanced tools for data validation, and ensuring the integration strategy is flexible enough to accommodate workflow modifications and unforeseen costs.

How do additional costs arise from data integration errors?

Additional costs can arise from correcting errors, performing additional data cleansing, or making workflow modifications. Unforeseen costs may also emerge from disruptions to business operations or the need for emergency interventions to restore data accuracy.

What role do advanced tools play in improving data integration?

Advanced tools are critical in enhancing data integration by automating quality checks, providing timely and accurate insights, and facilitating real-time data processing. They help reduce the risk of errors and ensure that data integration efficiently supports business objectives.

 


About the author

Beate Thomsen, Co-founder & Product Design

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As co-founder of the Rapidi Data Integration platform, Beate has spent over 15 years on its development, building it around her motto: 'keep it simple, functional yet beautiful.'
Rapidi is resetting the standards for simple, secure fast data integration.  Learn more now
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THE RAPIDI TECHNOLOGY  At Rapidi, we make data integration and replication easier, faster, and more  secure.  Why the Rapidi technology is different:   * No programming needed.   * Easy to implement and simple to use.   * Robust and yet flexible.   * Our RapidiConnector encrypts data to keep your data safe.    * Scalable to fit your needs as you grow.   * Can be used out-of the box or customized to fit your needs.   * Top-rated support. 

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