Over the years, businesses of all sizes and in all sectors have migrated to the cloud with a vision to reduce infrastructure management and focus on core business activities. With time, all system processes including development, testing, and integration have a ready-to-use module in the cloud.
Integration Platform as a Service (iPaaS) standardizes and fastens the data integration capabilities of a system. iPaaS lets enterprises build a single platform that connects and manages different data sources located in-situ or on the cloud. This platform brings together everything by integrating all the devices and syncing them in an optimized and unified way.
The market size for iPaaS is a testimony of the growing demand for on-demand integration services. As per Grand View Research, the market is expected to reach $2.7 billion by 2025.
As a result, businesses can expect more from the iPaaS solutions in the market. Ideally, the platform should enable organizations to add multiple capabilities to their business landscape. These customized iPaaS solutions often include enterprise-level security, scalability, support, and availability. iPaaS solutions should also support any type of data integration requirement for related teams and work in sync with other technologies.
However, iPaaS has its own share of challenges. IPaaS solutions must work for multiple scenarios, such as B2B (business-to-business) integration, A2A (application-to-application), CSI (cloud service integration), MAI (mobile application integration) and of course the Internet of Things (IoT).
Continuous increase in data volume
Data insights and an increase in data volume go hand in glove. If you manage the latter, the combination becomes an advantage. Elsewise, prepare to lock horns with issues of all types. Since an increase in data is inevitable, enterprises must build and manage a platform that can scale with the business while delivering qualitative data insights.
Ensure cross-functional availability
Numerous roles and departments within a company rely on data for their day-to-day activities. This underscores the importance of a data integration solution that is accessible, functional, and user-friendly. Although training and hiring skilled professionals can create a burden for a company, adequate data authorizations must be set in place to ensure that data is only accessible to those who are authorized to use it.
Connected systems in different landscapes
When different departments choose different data integration systems, synchronization errors can result. This is primarily because various tools may not be able to integrate amongst each other or they may even speak a different language. Hence, an iPaaS platform must support data literacy and promote a transition to the cloud. This is perhaps the only way we can raise the challenge with new products and technologies.
Several companies choose to develop their connected system from scratch. This process is tedious, time-consuming, and more expensive than using a third-party service provider, but companies still do it in the hopes of creating a data integration system that works seamlessly with all networks and users. Surprisingly, they often struggle with data integration problems and thus must strive to keep up with the technological advancements.
A step ahead: Fabric-as-a-Service
Enterprise iPaaS requires a different approach altogether. Gartner has coined this as “EiPaaS”. By offering set rules, EiPaaS aims to shift integration management directly to data consumers, rather than IT. By being present on the public cloud along with on-prem or hybrid options, vendors have adopted a modern approach to EiPaaS based on a data fabric-as-a-service (FaaS) model. With a focus on easing use and distribution, FaaS works on the principle of identifying data assets as data products. In the data fabric model, every product is unified in its very own micro-database and is always in sync with all available source systems, making data accessible to all users.
One example is K2View’s data fabric, which defines and manages all products, customers, orders, suppliers, and any other entities as logical units. It does on the terms of either the data instances or the definition.
With FaaS you get a tried and tested product that is ready to be deployed in a few weeks. It scales linearly and provides you with a real-time view of any data product and helps you adapt to change in a jiffy. It supports both multi-domain MDM (in cloud, in-situ, or hybrid environments) and modern data architectures like data hub, data mesh, and data fabric.
Maintaining high availability and performance
For every given scenario in integration, both the consumer and producer apps need to be connected directly in a way that they are aware of each other’s presence, location, and/or address. Because of this relationship, any change, outage, or bug can impact the availability and performance of the consumers and producers.
Ensuring architectural agility
Every time a new integration point is installed the iPaaS flows need to be rewired again to accommodate the new point within the system. When this happens, all the performance characteristics of the new point make their way to the existing flow. This can create downtime, slowdowns, and even latency. As a result, this type of high-impact integration can decrease the marketing avenues, as bringing out new services and features generally impact the system and make it less robust and responsive.
These challenges can be overcome by adopting an iPaaS solution that offers automated data segmentation and test data management across a scalable architecture that can be either on-premises, in the cloud, or a hybrid model. This approach ensures architectural agility despite the changes to the integration setup.
Conclusion
Enterprises have an opportunity to take the next step with advanced iPaaS platforms. To accommodate the increasing influx of data, they should embrace the change and prepare for web 3.0. In stark contrast to traditional out-of-the-box integration solutions, iPaaS platforms can help to ensure that the entire application stack works in sync, with the need for all manual interventions completely nullified. This approach can make an organization less prone to errors while increasing agility and transparency in ever-changing business environments.
