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

angular for healthcare

The global healthcare sector has been embracing digital solutions for a while now. But to what end, one may wonder? Well, simply put, the sector has been quick to integrate digital solutions to help enhance the quality of patient care and operational efficiency.

5 Examples of Retail Digital Transformation

The retail sector has been subject to continuous advancement thanks to the changing needs and demands of consumers. And it is also a well-known fact that shopping experiences have and must mirror technological and societal advancements. Today, customer expectations are unequaled, demanding consistent and customized experiences across different platforms.

folder

Virtual Hard Disk (VHD) files play a role as they store all the data for a virtual machine. If these files get damaged or mistakenly deleted it can have repercussions, impacting not data integrity but also operational continuity.

management software

Corporate transparency is essential in building stakeholder trust and credibility in today's evolving business environment. As businesses grow and adapt to changing regulations, ensuring adherence to rules and maintaining records has become increasingly intricate.

How Salesforce Financial Services Cloud (FSC) can transform Insurance Operations?

Among the solutions developed over the past few decades, Salesforce Financial Services Cloud (FSC) has emerged as the definitive choice for gaining flexibility, visibility, and long-lasting, inclusive growth in the financial sector.

open source

Open source software (OSS) is distributed with its source code, which means it can be distributed, modified, and used freely with the original rights. Most users never see the source code, a critical part of the software. 

Dynamics CRM

It's one of the keystones, basic but key in the successful highly competitive modern business environment, where the connection with the customer is a must.

Python for small scale businesses

The speed of progress in the modern business landscape is quite relentless. For small-scale companies, this implies that keeping up with this progress is not simply gainful but fundamentally significant for their survival. And what does success in such an environment demand?

Benefits of Power Automate for the Finance Industry

The finance sector needs to battle many difficulties in the modern and quick-moving digital landscape. Be it exploring the unpredictable snare of official guidelines or overseeing tremendous volumes of data - - financial establishments are feeling the pressure to succeed. This demanding environment, in turn, often leads to exhausted teams, costly manual errors, and inefficiencies that can be chalked up to repetitive tasks