How to Avoid Failures in Data Integration Projects
Businesses suffer from an overwhelming amount of data giving some the challenge as to how to handle it. They look for a robust data integration platform that can take their data sources under full control, ensuring all the business processes will go smoothly and without any potential risks. Highly data-driven companies are ahead of their competitors since they get more advanced analytics and predictions which foster their decision-making. What’s interesting, as per PricewaterhouseCoopers, business decisions of 61% of companies surveyed claimed they rely on intuition, rather than data, which risks putting them beyond their competitors. That’s why data integration is so vital for data-driven decisions.
Selecting an appropriate data integration tool is only a part of this challenge; you also need to consider pitfalls that your data integration project can face.
Why Data Integration Projects Fail: Challenges and Pitfalls
Along with your desire to find a proven data integration solution to ensure success, you also need to develop a strategic plan. The following pitfalls can negatively affect your integration process if you do not take them into consideration beforehand.
5 Factors of Successful Data Integration
Considering all above-mentioned pitfalls of data integration, you can take effective measures while planning your data integration project:
Evaluate data quality
Poor data quality is one of the biggest challenges for data-driven companies. Before integration, it is vital to check the data quality of different sources since the poor data of one database can be contagious to another, even if it was in good shape before. Corrupted data causes inaccuracy of data and harmful effects.
It means your company needs to be ready to scale. If the number of transfers between systems grows and you need new business processes, your integration platform has to handle these challenges. Thoroughly think about which solution to choose: custom-made interfaces or ready-made data integration platforms with pre-configured templates. One solution can seem the most appropriate to your current needs, however, it can be not so reliable in the future. If you develop custom-made integration it can limit your possibilities of additional integration and it can result in a time-consuming, complicated, and costly process.
Ensure buy-in and top management support
It is vital to have the right team on board. Considering the fact that data integration will have a broad impact on your organization, it is important to involve outside IT members from other departments, including senior leaders, data analysts, and project managers who have a well-rounded collection of skillsets.
Custom integration needs additional modules and features that are usually hard to maintain, especially when you have to integrate different systems. An excessive amount of new and altered functionalities can affect your budget and time resources. You need to think in a long-term perspective: when your business scales, you might find you need additional functionality that is not supported by custom-made solutions. For example, if you need scheduling, monitoring, error-handling features data integration platforms such as Rapidionline have them built-in.
Think about minimizing errors
Data transfer is a challenging process that can compromise your efforts if not managed correctly and if it lacks transparency and control. Data integration platforms have integration templates, including mappings and migrations, allowing them to minimize errors. Moreover, such platforms have a log with data about all the transfers giving you a full picture of the problem. This allows you not only to resolve the issue at that very moment but also to prevent new errors in the future.