Application Integration VS. Data Integration: How Do They Differ?  

Application Integration VS. Data Integration: How Do They Differ?  

  • Post author:
  • Post category:Data Integration
  • Post last modified:April 29, 2022
  • Reading time:9 mins read

Handling data is the core activity of both application and data integration. The main goal is the same: make the data usable, accessible and functional for the data users. The processes translate data from several sources and transform it into a new data set.

Although data integration and application get treated as one and the same, it’s an incorrect conception and can lead to miscommunication inside the organization and one of the processes can be neglected all at once, when both should be working together towards the goal of making the data set accessible.

Most companies have application integration and data integration as cloud-based solutions in order to keep accessibility and scalability easier to achieve. But both solutions can differ a lot, especially when it comes to the use each company gives to them according to their needs. So, to avoid miscommunications and ensure that your company is giving the best use of these solutions, we will go through both processes and explain how they differ. 

What Is Application Integration?

When a business works with multiple applications, the data must move from one application to another with ease in real-time or very close to it. So application integration is what creates the connectors between those applications, so they can work with one another.
By unifying the application’s workflows, the data will be merged, and the company can see what’s happening in real-time. It’s the best way to eliminate data silos and keep the efficiency high between the departments using the data within the organization – as the information care be seamlessly shared.
Application integration is also used as a way to connect the cloud-based applications to the current on-premise systems that the company already works with, so data users can bring the existing data to newer tools and technologies.
With application integration software, data can be sent between several OLTP (online transaction processing) applications – and the company is the one deciding which one will be the source and which will serve as the destination. To make this process work, it’s crucial to know about application logic, as the users must understand all the ways the company uses its data, so then they can use application integration to see events and actions immediately as they occur. 

The Benefits Of Application Integration

Some main benefits of application integration are:

  • Increasing efficiency and saving time: integrating the data from the applications used by the company will minimize all the laborious work of transporting the data manually between applications. Instead, the process will happen automatically and in real-time; 
  • Adding value to the data: combining applications and making work more efficient will make the data much more valuable as the users can easily access and take the insights they need from it;
  • Better information exchanging: connecting applications throughout the company will make the communication flow better between the departments and will eliminate the silos that keep the teams from sharing ideas. Application integration is the way to create collaboration;
  • Increase data visibility: the point-to-point integration that happens with application integration will give the users the opportunity to observe and measure the data across the data flow, enhancing the visibility and increasing the chances of acting on the data before any issues appear.

What Is Data Integration?

By contrast, data integration is the process of taking the data from multiple sources and combining it into a single data repository or data set. But data integration is more than moving data from one place to another, it’s also a process to make data usable by taking unstructured data from several sources and creating valuable new data sets.
With structured data in place, it’s possible to understand better the business operations with the help of analytics and identify innovation opportunities. 
Data integration works by replicating data into a data warehouse, and this way, besides the possibility of analytics and reporting, the data can also be used for migration and other needed consolidations. 
Most companies usually let the jobs be programmed to run according to their needs – every hour, twice a day, a few times per week, and so on – it all depends on how quickly the data needs to be updated. It’s rare to find companies making data integration happen in real-time instead of processing per batch, but it’s not impossible. The main issue is the cost involved, which makes it not worth it, so keeping it periodically will serve most purposes just fine.
The basic function of data integration, which is taking the data from the source, transforming it into a usable format that can be recognized by the destination application and then loading it into it, is called ETL (extract, transform and load), and it’s also a way to eliminate data silos and keep the data users making the most of the information available. 

The Benefits Of Data Integration

Some main benefits of data integration are:

  • Making data accessible: data integration combines the data from several sources in multiple locations in one single and unified view, leaving it much easier to comprehend and analyze, giving the company powerful insights that will help on innovation, growth and revenue.
  • Increase competitiveness: with the data integration process and strategy in place, the company can focus on looking for the vital parts of the business and create an action plan to act on that. And this can lead to a major increase in competitiveness. 
  • Getting better insights: as mentioned above, the unified view of the data will make the decision-making more successful as the insights will be taken from quality data with accurate information.
  • Increase data quality and integrity: data integration acts directly on incompatible and incomplete data, minimizing the errors that can affect the ability of the company analyzing it – most data integrity tools can identify low-quality data and fix it.

The Difference Between Application Integration And Data Integration

The main difference between the two processes is in the speed at which the data gets transformed and the size of the data set. Application integration works in real-time with smaller data sets, so it gives the company the ability to respond faster to new information or any issues regarding the data and performance – they can start mitigating the issues as soon as they occur. 
It also allows the company to easily access the data in the application instantly, even when this information is being handled in different locations or being updated by other departments.
The data integration process is usually done in batches by most companies and often after other processes have been completed in order to keep the data quality by removing duplicated information. Data integration can be performed with massive data sets and be fully automated to happen as soon as the data gets created.
Both processes also differ when it comes to how they are managed. Application integration is normally managed as part of the company’s software development and operations, so their applications can be connected with efficient workflows – and this can happen with existing platforms or custom integration platforms created for their specific needs.
Meanwhile, data integration is managed as a process for data used for business purposes, so the orchestration is usually not part of the company’s overall software development.

When To Use Application Integration And Data Integration?

Data integration is the process for companies that need to analyze their static data after combining it in the right format to fit their systems, while application integration is used to see the data changes in real-time and make the needed interactions with it. 
Application integration will fit better when the company needs speed to deal with the information, while data integration shows the data in an accessible and consistent single view after the integration happens, making business intelligence and insights easier.
Data integration will keep the data accurate, but it’s much slower than an application integration process, which allows the data users to capture issues in real-time and act immediately on them. 
Some companies do prefer to have both processes running inside their data flow – in different stages of their data cycle – as having access to quality data from several sources in a unified view while being able to immediately perform changes on it in other stages is the way to enable innovations. 
There’s no better or worse approach, they are both fit for different purposes. Application integration can be seen as working with data at an application level, while data integration is on the database level.