Resource Data

Why data integration is integral to successful businesses

As companies look to get the most out of their data, they need to consider the benefits that data integration can bring to their business, especially as more and more organizations undergo digital transformation.

As companies have embraced more digital assets to power their businesses, there has been a corresponding increase in the amount of data they need to manage. Global organizations generate approximately 2.5 quintillion bytes of data every day. As digital tools become a bigger part of the fabric of our workplaces, especially with the rise of the cloud, businesses are faced with the challenge of keeping up with the growing amount of data they generate. A business may adopt a range of applications and software that generate data, which is typically stored separately, making it more difficult to leverage the information to improve business operations. This is where data integration comes in.

Data integration gives businesses more power to leverage the data they create and ensure it is free of errors or duplicates. The rise of business apps and other digital tools, as well as the shift from on-premises data storage to the cloud, have made data integration essential for businesses in several ways.

Accessibility

Accessibility is one of the most visible benefits of data integration. By bringing all of their data together in one source, it is easier for businesses to leverage information effectively. Being able to access data more easily is key to unlocking other benefits of data integration and eliminates the amount of work required to bring together data from multiple sources.

Followed

Data integration also simplifies tracking. With all the data compiled together, organizations have a better overview of the situation throughout a business process. For example, through data integration, a company can see how a customer is progressing through a sales funnel and what actions they take along the way. Without data integration, information about a customer’s behavior could be confined to the marketing messaging platform, user information database, and advertising platforms the company uses to market. user acquisition.

Reports

Similar to tracking, data integration enables better reporting practices for businesses. Instead of going to different sources to access and collect data, it allows IT teams to streamline their reporting needs since they can run reports and enter what they need from one place. . Data integration also improves reporting by providing a more comprehensive view of all applications, software, and systems.

Overall, data integration is a powerful resource for putting a company’s information at the fingertips of executives, helping them make smarter and more informed decisions, improving their agility and the ability to identify areas of success or improvement in a way that was previously not possible or impossible. easy access.

Data Integration Challenges and Risks

Considering all the benefits businesses can derive from it, organizations should be aware of common issues that can arise, such as data import, data export, data formats, or lack of automation. It goes without saying that data integration is only useful if the data itself is complete and accurate. Errors from missing fields or incorrect entries can have a significant impact on business operations.

For example, customer success teams could quickly lose the opportunity to improve the customer journey if customer engagement data from different sources is not aligned. In a sense, inaccurate data is worse than no data at all, because inaccurate data can lead to poor business decisions or misunderstandings that prevent the business from improving its performance.

Mistakes made during the onboarding process can be very difficult to reverse or reconcile. Companies concerned with managing an integration should consider the benefits of automated tools to ensure a smooth transition.

Automated tools support

Managing a data integration project should not be taken lightly, given the cost of working with incomplete information or data that contains errors. By using a packaged system, MSPs and IT managers can track the movement of data and support successful integrations and data recovery as needed. Onboarding tools help carefully map out the path from point A to point B, and many also offer preventative tools that can help businesses ensure their data is successfully onboarded.

Loss of data during an integration represents a significant risk for companies that want to make the most of the data they have. Fortunately, automation tools can establish methods to prevent data loss during the transition, such as a publish/subscribe model, which creates copies of data on demand instead of sending the original data. Staging areas create space for verified data to wait before being loaded. Additionally, some onboarding software can help companies establish receipts that provide a way to document how data is used or moved to ensure it isn’t accidentally deleted or improperly modified.

There is a notable difference between common data transfer approaches that companies should be aware of when looking for an integration software vendor. Traditionally, data integrations are approached via the “ETL” method (extraction, transformation and loading). This process moves data from a source system to a warehouse or other system and allows data to be manipulated in the middle.

However, the “TEL” (transform, extract and load) process is more efficient because it gives you the opportunity to transform or modify the data before it is moved. Changing data in the middle of the integration process does not always create the desired result and can lead to more problems once the data is loaded.

As companies look to get the most out of their data, they need to consider the benefits that data integration can bring to their business, especially as more and more organizations undergo digital transformation. While managing a large amount of data can be cumbersome, there is also a lot of valuable insight to glean from enterprise data.