Enterprise data integration technology has undergone a seismic shift in the last few years. Back in the day, it used a point-to-point approach to integrate applications or systems across organizational ecosystems that were time-consuming and complex. Presently, integration methods have evolved into using an API-led approach that speeds up integration and allows organizations build an infrastructure rich in productivity, agility, and control.
Though modern integration solutions help companies maximize business outcomes and achieve their goals, not all of them can match up with rising expectations. To pick the best, enterprises need to keep several points in mind.
Enterprise application integration has become more cloud-based. It exposes SOAP/REST APIs for data as well as metadata management that is based on business services and business objects.
Much different to the previous generation of on-premises applications, the current SaaS applications do not offer direct access to the respective database behind their services. Consequently, these applications do not have access to a relational client-server interface used by previous generation application integration. Modern data integration platforms offer simple ways to utilize REST and SOAP. They can easily abstract complexities of these APIs into business actions along with objects for allowing an application administrator to integrate services proactively.
Enterprise IT-based business ecosystems are shifting from bespoke data warehouses to agile data lakes wherein, all the data available on a Hadoop cluster are stored. With the advent of technology, companies today are making use of low-cost and low-administration alternatives to analyze large volumes of data (along with the 4Vs) for better decision-making and improved infrastructure.
Traditional data integration engines are limited. They are either optimized for batch processing of large-scale data or continuous data streams. On the other hand, modern integration solutions support data velocity irrespective of the size of data. With an engine that can stream large-scale data such as sensor data from the Internet of things, modern data integration platforms can consume and timely deliver responses to different business events.
Conventional integration platforms use a clock-driven approach, but modern ones use an event-driven approach. The event-driven methodology is far more beneficial than the clock-driven one. It is more efficient and makes sense in this real-time enterprise world as companies can gain access to data in real-time which is more accurate and free of discrepancies. In addition, the need for clients to ask repeatedly even if a given system has new data available or not gets eliminated completely.
Conventional integration systems fail to provide absolute connectivity as they rely on a point-to-point approach. While, on the other hand, modern integration platforms use API-led connectivity approach that helps organizations create an integrated, connected environment through discovery, self-service, and reuse. Modern integration solutions use API-led connectivity technique to decentralize and democratize access to the data for increasing agility, speed, and productivity. Additionally, modern integration platforms are embedded with many prebuilt connectors to accelerate implementation for taking care of new integration scenarios.
As the current world of business has become more and more cloud-based and data-driven, integration technology must be delivered as a service. Modern integration platforms are available as a service for allowing access to anyone who needs data rather than only a few practitioners who toil away in the back room. Their ability to empower “citizen integrators”—through a self-service approach has allowed users meet a broad spectrum of needs with ease and precision.
By keeping the aforementioned points in mind, you can help your business corner the landscape without putting much effort or money.