Application Integration vs. Data Integration: Purpose, Pros, Cons & Everything in Between

Application Integration vs. Data Integration: Purpose, Pros, Cons & Everything in Between
Photo by Manuel Geissinger from Pexels

Businesses need to plan and prepare before digitizing operations to survive and thrive in a dynamic business environment. If you want to get things right from the start, it is essential to know the basics of integration technologies. 

What is Application Integration?

Application integration is the fusion of information and workflows from different apps. Digitization of operations exerts a compelling need for companies to integrate cloud and on-premise apps. App integration facilitates seamless interoperability and orchestration of data for generating real-time insights. 

What is Data Integration?

It is the approach of retrieving data from varied sources and collating it to create a unified layout. Data integration solves the complications of merging different apps to stay on top of data assets. It enables users to extract value from the integrated interface. 

Data integration can be further classified into two categories - Operational and Analytic 

Analytic DI is applied to business intelligence and data warehousing. Operational DI is ideal for synchronization, consolidation & migration of active databases. It also facilitates data exchange in a business-to-business situation. 

In simple terms, DI is the mechanism for merging data between databases, and app integration is for handling data between applications. 

3 Key Differences Between AI and DI 

1. Efficiency vs. Effectiveness: 
Data integration is a scheduled, batch mode procedure that attends to the data at rest. It is why it calls for a sequence of data-intensive approaches. It involves standardization, manipulation, duplication, and reconciliation of data in batches. A data integration task can be run once in a day or a week. However, it cannot be run several times in one instance to get accurate insights into business performance. It also takes a considerable amount of computing time to generate compliance data and identify anomalies. 

App integration facilitates real-time communication of live data between apps. The information only changes hands between different apps, following a two-directional orientation. The amount of time taken and data involved in enterprise application integration is modest. It deals with different app connections at the workflow level, with information being the focal point of transference. 

2. Transferable vs. Transformative:
App integration works at a service level framework for the timely movement of data. This data flows between applications through an execution process that may be synchronous or asynchronous. In short, enterprise application integration facilitates business operations that traverse across independent applications. These processes are transactional and entail a level of abstraction between the allied business operations and basal applications.

As opposed to this, data integration is a transformative process. It stems from the deployment of relevant databases and the need to transfer data between them. The main goal of data integration is to colonize a warehouse from different transactional mechanisms. The data is extracted from databases and collated to form a unified system of the collated information for analysis. Data integration creates a layer of abstraction from the rudimentary sources. It also includes extrinsic data that lies within the sphere.

3. Clear-cut vs. Consolidated: 
Enterprise application integration runs in a predefined architecture. This approach is adopted to synchronize the associated apps in real-time. It also facilitates the maintenance of integration until the end of the procedure. For instance, in a P2P business process, a company procures raw materials from vendors. This process starts with the issuance of requisition orders for purchasing raw materials. It further proceeds to the next stage where a purchase order is created. On the receipt of goods, the documents for order confirmation and shipping notice are framed. Finally, an invoice is generated for the payment and the transaction is updated in the accounting system. This complex process spans across several application systems and external sources. As a Procure to Pay business process may involve outsourcing, the events need to be executed in sequential order. It creates interdependence due to which there is stringent opposition to overlapping. And, it is where the clear-cut architecture of enterprise application integration emerges as an ideal solution. 

Data integration runs through the data cluster from end-to-end but publishes only relevant data to the user. Large organizations have scores of integrated applications. It makes access to difficult independent interfaces. Data integration is helpful in such cases for quick and easy data access. 

Conclusion

If you're still wondering which approach to take, it's essential to know that each is a perfect fit for a different purpose. Data integration combines data sets from various sources—app integration, on the other hand, converts and shares data between applications. 

Accordingly, enterprise application integration is ideal for working with data at the application levels. And, data integration is perfect if your business is operating at the database level.

Similar Articles

Drupal and Salesforce: How This Duo Benefits Businesses

There is no doubt about the fact that customer relationship management (CRM) software serves a critical purpose across organizations. It is no matter the industry they may be operating in. After all, they are essentially the connecting link between businesses

Magento vs Drupal Commerce: Which Web Development Platform is Better Suited for You?

Why we develop websites or why they continue to be pursued so ardently is a dated question, because it is pretty clear for anyone to see the role they play in the business world. But this question gains completely new importance when one speaks of eCommerce because here, websites are not merely meant to share information about the company.

Robotic Process Automation (RPA)

In my opinion, Robotic Process Automation is a level ahead approach that produces more beneficial support than test automation in different ways. Learn more in this article.

Why You Should Switch to the Cloud

A 2019 Gartner report about the revenue generated by cloud computing found that the global market for it was expected to touch roughly $250 billion in value. By 2022, Gartner predicts, the worldwide public cloud service revenue would reach a massive $331 billion market value by 2022

Issue Tracking Tools

Issue tracking is one of the most important parts of a software development lifecycle that cannot be skipped or omitted. While organizations emphasize on increasing their software testing efforts to improve quality and ensure faster releases, their dependency on tools increases too.

UFT Test Automation Frameworks: What You Need to Know

As the importance of software continues to grow, there are several factors whose influence have grown right along with it. And out of all of them, test automation frameworks have garnered their fair share of attention from the market. Why is that?

Top Ways in Which EHR Systems Enable Better Patient Care

Electronic Health Records system offers benefits that have enabled an industry as tricky as healthcare. The software allows for medical professionals and other professionals across the ecosystem to quickly input as well as access information about a patient.

Why You Should Choose Angular to Build Web Apps

Development, while eventually rewarding, can be a very tedious process. But that’s the thing about technology; it always manages to find a solution, no matter the problem. So, in the context of development, experts came up with frameworks that would help programmers do away with tedious and arduous coding practices.

Issue Tracking System in DevOps

DevOps and Agile approach in an organization is not merely an implementation of certain tools and techniques, instead, it is cultural change. Many organizations in the software industry have either adopted these methodologies or are making accommodations to incorporate them in their system.