What is EAI?
Enterprise Application Integration (EAI) is the process of uniting databases and associated workflows with business applications to ensure that the business uses information consistently and that changes to core business data performed by one application are correctly reflected in the others.
Why is enterprise application integration important?
Most businesses use multiple software products from different vendors in their day-to-day operations. These apps can have different uses, data stores, and modes of operation. This can create data silos where data is either duplicated between databases or available in one but not the other. This leads to data inconsistency when users have to manually copy and paste data between applications. Users may also need to consult several applications for their daily work.
EAI provides a methodology that helps these disparate applications share data and workflows to reduce manual steps and errors and provide better insight into organizational data. This becomes more important as the organization grows and technology advances.
Previously, all business workflows were manual and performed on paper. As computers automate the work of users, the daily tasks of information workers have quickly become formatting data and transferring it from one system to another. This need to quickly make data available between applications will only increase as more organizations adopt microservices, software as a service (SaaS), and platform-as-a-service tools. (PaaS).
EAI can help eliminate manual steps and reduce user error.
How does enterprise application integration work?
EAI is a director or philosophy towards the programs used in a business. It is not a specific tool or framework. It is better to consider it as a goal or an ideal to be achieved rather than an implementation.
Organizations can be at different levels of EAI, from separately existing applications to fully integrated where all applications share common data and workflows. More realistically, most will fall somewhere in between, with some apps working together and some not. Businesses are constantly changing, so any EAI implementation must also be able to change.
EAI does not require someone to reprogram the applications themselves. Instead, organizations typically use middleware or APIs to make applications work together. EAI also makes it easy to interchange applications to meet business needs without affecting productivity or requiring large-scale system designs.
Not specific to cloud or on-premises, a well-done EAI implementation can accommodate applications with different sources and underlying infrastructure needs. EAI attempts to solve the same business problems as using a single enterprise resource planning (ERP) software package, but with multiple smaller programs working together instead of one large program.
Almost every organization uses some form of EAI. Taking the exit from a program and running a Microsoft Excel macro or script to reformat it to enter another program can be considered a simple form of EAI.
Objectives of enterprise application integration
Database integration is a common and relatively easy goal for EAI. Eliminating data duplication and consistency across applications can reduce errors and liability. EAI can be achieved by configuring different applications to use the same database or by using synchronization tools to keep different databases up to date with changes. Data warehouse designs can make this possible. All of these can also be more easily integrated with big data systems for better business intelligence (BI).
Workflow integration can allow separate tools to work together to increase productivity by making it easier to complete common tasks. As an example of EAI, an employee onboarding may require human resources to update payroll, personnel records, office assignments on a floor plan, access controls to gates and computing resources. With EAI, all of these different tasks can be accomplished as a single workflow rather than in separate programs.
Interface integration allows organizations to present a single consistent user interface and user experience (UI and UX) to operators instead of multiple interfaces from different software packages. This can be the most difficult form of EAI to perform as minor changes to the underlying software can result in redesign work.
Types of enterprise application integration
An EAI implementation depends on the underlying tools and goals of the project, but several common design paradigms have emerged.
Point-to-point integration. This is the simplest form of EAI. In this document, data is extracted from one source, perhaps reformatted, and then ingested by the next application. These are often simple to implement for small workflows and a few tools. However, they can quickly become large and difficult to manage as new applications and integrations are added, and can become slow as a backlog or slowdown in one system affects others in line.
Star integration. This approach uses a central program to facilitate data and steps between requests to participate. The program can handle data reformatting and keep workflows moving when the application slows down. Hub-and-spoke is therefore faster and more reliable than point-to-point, but requires development time and effort to set up and maintain.
Bus integration. It is an evolution of the EAI star design. It is also called Enterprise Service Bus (ESB). In a common bus design, all participating applications use a set of standards for sending and receiving data or workflows. This allows for quick and easy integration but requires work during the planning and product selection phase.
Middleware integration. It involves an intermediate program that sits between the end user and the underlying application. Middleware supports interface integration and can have a star or bus underlying design.
Microservices. They are small, single-use tools that support EAI initiatives. These can be serverless functions or dedicated applications designed to easily or quickly integrate connected programs. Microservices can often be easily offloaded as cloud workloads.
To explore 3 best integration frameworks and what automated implementations of data integration.