Five Data Integration Methods & Their Pros and Cons

Today’s businesses are data-driven. Every bit of information becomes data, and volumes of data from disparate sources become an invaluable treasure. The term Data Integration is indispensable when it comes to anything that’s data-related. By leveraging data integration, companies can access and utilize relevant data more efficiently to drive better business decisions.

Now here’s the million-dollar question: How do you integrate all your data? This article explores the five most common data integration methods and how each works. Let’s get down to the details.

A Brief Intro to Data Integration

Data Integration refers to the collation and consolidation from various sources into one single, centralized dataset or warehouse. Data integration, however, extends beyond mere data consolidation. The process enables:

• Easy, authorized access to data
• Accurate analytics to make sound business decisions
• Monitoring of Key Performance Indicators
• Integration of data legacy with business intelligence applications
• Better understanding of supply chain operations and financial status

Since there is no one-size-fits-all approach to data integration, deciding how to implement it can take time and effort. One must understand how data integration works and which approach fits best with their needs. Understanding the various approaches allows you to know what exactly is happening and how to overcome unexpected challenges.

5 Ways to Integrate Data From Disparate Sources

1. Manual integration

As the name suggests, manual integration involves no automation. Data managers manually collect, process, and store the data without any software. The entire process is done by data managers using a customer code.

• Lesser costs incurred with data integration software and hardware.
• Gives the user complete control over integration and management.
• Easy to use and maintain with a small number of data sources.

• Highly error-prone and not viable for complex integrations or big data queries.
• Not scalable for larger integration projects since it is very time-consuming.
• Not easily accessible as it requires a manual code for everything.
• Not user-friendly for other team members

2. Middleware integration

The term “Middleware” refers to software that is used to connect applications. Once connected, the software enables data transfer between the applications and their databases. Middleware is ideal for businesses integrating traditional and modern systems, but it's mostly a communications tool with limited capabilities to analyze data.

• Enables easy integration of legacy systems with modern ones.
• Improves communication between network systems.
• Transforming and transferring enterprise data is automated and consistent.

• Not compatible with all data systems.
• Quite expensive as it requires a data developer to handle the process.
• More reliable mainly for data analytics.

3. Application-based integration

The app-based approach is self-explanatory- A software application locates, retrieves, processes, and consolidates data from several sources, making it compatible to work with. This approach is ideal if your organization has both on-premise and cloud-based data sources because it can easily optimize the workflow between diverse data environments.

• Diligent use of resources because it is fully automated.
• Easy data transfer between diverse systems and destinations.
• Scalability to adapt to the increase in data consumption.
• User-friendly and easy to handle.

• Requires applications to integrate all the data and sources, limiting its capacity to deal with large volumes of data.
• Application deployment and maintenance procedures require technically-sound data analysts or managers.
• Businesses that offer this as a service use unstandardized approaches.

Also Read: Mastering Data Integration: The Ultimate Guide

4. Uniform access integration

Uniform access integration is famous for its ability to locate, retrieve, process, and consolidate data from disparate sources while allowing the data to stay in its original location. This approach enables customers to retrieve data quickly and efficiently while still leaving the data secure and safe in the source system.

Using this technique, organizations can have access to multiple disparate systems without the need to create backups or copies.

• Does not require separate storage requirements because the data stays in its original location.
• Creates a simple and unified view of data. Synchronizes well with multiple sources and data systems.

• Multiple access to sources can compromise the integrity and quality of data.
• Frequency and number of data requests are beyond the scope of the host systems.

5. Common storage integration

This data integration works similarly to uniform access integration. Unlike uniform access, which does not require a storage location, this approach creates, and stores consolidated data in a warehouse. Businesses that want to maximize data utilization prefer this type of data integration.

• Lesser burden on data host systems by eliminating the need to store data sets in multiple locations.
• Uniform data appearance to identify trends and patterns in the data and reduce time spent on manual analysis.
• Greater accuracy and reliability in analysis, ultimately yielding better decision-making.
• Better opportunity to leverage effective analytics and gain deeper insights into the data.

• Unless businesses are prepared to spend generously on additional storage plans, the large data volumes can strain their IT budgets.
• Besides storage costs, maintenance costs will be an additional burden unless you opt for a third-party data warehouse.

Closing Thoughts

In conclusion, data integration is a critical aspect of becoming a more data-driven business. Trueloader understands that the success of your business depends on your ability to leverage your data effectively. With our expertise in various data integration methods and technologies, we can help you design an integration strategy that aligns with your business objectives and meets your data integration needs. Contact us today and take the first step towards achieving a more unified and efficient data system for your business.