Application Integration Vs Data Integration

Application Integration Vs Data Integration


Business organizations generate a large volume of big data daily. Managing data through application and data integration is one of the best practices for modern businesses. The easiest way to make data more accessible and functional for end-users is to implement these best practices. Both application and data integration translate various data sources and transform them into a complete set of data. They are typically cloud-based to offer the accessibility and scalability of cloud computing. Data integration is completed in batches with a focus on creating new data sets that reveal business insights. Application integration creates better workflows and efficiency in daily operations.

What is Application Integration?

Enterprise application integration allows individual applications to communicate, exchange data, and invoke their offered services. Application integrations are the backbone of any digital transformation strategy. When individual applications are integrated and can communicate, organizations can find new and innovative ways to operate.

Business applications traditionally live in data silos where they function independently of each other. These applications are necessary to execute business processes or gain insights into the organization’s performance. Since non-integrated business applications can’t communicate, they must be manually disconnected, and the data must be moved manually. This is time-consuming and increases the risk of poor data quality and errors.

Application integration tools eliminate the need for manual intervention. Integration technology allows business processes to execute more quickly and with minimal errors. The services across different applications can be combined to create a more accurate and real-time view of business functions. This results in greater agility and speed when reacting to changing market demands.

Today’s integration technologies include an application programming interface (API)-led approach combined with event-driven architectures. Integration can take place between a combination of on-premises applications, cloud applications, edge devices, and online web services. The more that organizations use SaaS applications, the greater the need for application integration.

What is Data Integration?


Data integration is the process of combining data from different data sources and formats into a single data set. Business data integration makes data more usable by taking structured and unstructured data from different data sources to create new, valuable data sets. This improves the capabilities of data analytics and results in deeper insights and new opportunities for innovation.

At the core of data integration are extract, transform, and load (ETL) capabilities. Performing batch integrations and real-time integrations, as well as the use of automation to address errors, is the easiest way to eliminate data silos and leverage the full power of business data.

Integrating big data has several advantages. Making data more accessible by creating a single view results in comprehensive insights that help organizations improve collaboration and innovation. Greater insights help improve business intelligence and aid in key decisions that will improve business processes. Integration tools increase data integrity by identifying low-quality data.

What’s the Difference?


The main differences between these integration processes are the rate at which data is transformed and the amount of data that are transformed. Application integration works in real time using smaller data sets so that actions can be taken as new information becomes available or performance issues occur. Business users also have instant access to data even when it’s being updated.

Data integration takes place in batches to eliminate redundancies and ensure data quality. This process uses large sets of resting data and takes place once the processes for creating data are complete. DevOps are responsible for managing integrated applications. They connect applications to create efficient workflows on existing integration platforms or by building custom integration. DataOps are responsible for data integration and ensure the management and orchestration of data for business uses.