When intelligent technology is put into the hands of smart users, they can “leap tall buildings in a single bound.” But most application and data integration technologies are built for developers only, widening any existing disconnect between the speed of business and the reality of over-subscribed IT resources.
The right integration technology can allow all users — application and data integration developers and architects, BU project owners, and business users — to pursue new opportunities faster than previously imaginable in today’s best-of-breed enterprise software environments.
A checklist for self-service
- Ease of use is the paramount consideration for self-service, the definition of which varies by audience. The checklist below will help you to choose an application and data integration solution that addresses the complete spectrum of self-service requirements.
- A rich, cloud-based user interface is the basis for self-service; all users can benefit from an intuitive, graphical toolbox that is web-accessible through any device.
- One platform for all types of workflows consolidates data, application, and process integrations, ending the silos perpetuated by legacy integration technology.
- Snap-and-assemble pipeline flows dramatically speed integrations, replacing manual integrations with a low- or no-code approach. In this way, many integrations can be performed by citizen integrators, reducing heavy enterprise developer requirements to a lean- or no-developer model. Developer resources can be redeployed from tedious integration and maintenance tasks to higher-value activities.
- Advanced monitoring ensures that any integration exceptions are caught and addressed prior to production, establishing self-service as a viable enterprise best practice.
- Support and resources are important catalysts in self-service adoption. The application and data integration solutions provider should offer resources such as an integration Health Check, Community, Service Support, Documentation, and Training. If needed, the provider should also provide access to trained service providers and partners.
- Artificial intelligence (AI) and machine learning (ML) are advanced technologies that are the basis of futuristic robots and game-changing predictive analytics. Perhaps surprisingly, AI and ML play an important role in furthering application and data integration self-service, as well; these technologies allow users with vastly differing skill sets and technical skills to employ the same application integration platform.
- Properly applied, AI- and ML-enhanced application and data integration platforms can deliver individualized ease of use, and present the appropriate interface, documentation, and support options to improve users’ experience and productivity. Importantly, ML and AI can automate tedious, repetitive tasks by suggesting configured next steps, checking for errors, and identifying opportunities to optimize integration pipeline performance. These capabilities further empower users with skill levels ranging from “citizen integrator” business users to expert application integration developers.