In a 2014 study, companies were found to run an average of 508 apps each. This number has undoubtedly increased over the past few years as companies become aware of the tools that can add value. There remains, however, a crucial problem. For the most part, apps aren’t designed to communicate independently with each other.
Enterprise Application Integration (EAI) is the solution to this problem. In some scenarios, the middleware collects incoming data and passes it to relevant applications. In others, applications are linked by connectors that allow them to communicate directly with each other. Automating the communication process between commonly used applications can play a crucial role in data analysis.
When an individual wants to download a new app on their smartphone, they are just one click away. Large organizations do not follow these rules and it takes time to migrate to a new system or integrate an upgraded CRM tool, for example. In an ideal situation, they want to deploy both the old and the new to give them a full platform of apps that can help them achieve their goals. Adding new apps while managing existing tools is often a preference, especially when compatibility is an issue.
Although data integration expressly deals with the flow of data from one system to another, EAI has an indirect impact, ensuring consistent access to data across these programs. In this way, users are not required to familiarize themselves with new software, but only with the tools that they use consistently. EAI software brings together the data or functions of one application with those of another where they already exist.
EAI may involve steps beyond middleware deployment. Additionally, stakeholders often develop protocols to modernize the way applications interact. This will include understanding how existing applications fit into the view once new programs are added. It also means that users will want to find ways to use data efficiently once new connections come online.
Adapting to an EAI framework gives enterprises a wide range of software choices for any use case. If all cross-enterprise applications can communicate with each other with little intervention, organizations gain independence from vendors. They can take a state-of-the-art approach to stacking technology as different branded applications can be integrated seamlessly. EAI consolidates business applications into a single framework for current and future use. By automating the workflow in this way, organizations no longer need to rely on a sneakernet or an email chain to do the work of the onboarding tool. This can mean a massive boost in productivity.
When you buy an EAI solution, it is imperative that it connects to all data sources in the organization. Without interoperability, organizations face the problem of data silos – pools of information that could play a useful role in analytics, but are isolated from EAI. Automation of communication between applications has slowly been incorporated into enterprise software. In the current scheme, EAI tools act as the glue that holds a company’s business processes together.