Key Findings

The keys to integrating applications and data are APIs, standards, knowing business objectives, providing an excellent user experience, and testing securely. It’s all about RESTful APIs. APIs are the de facto standard, but one size does not fit all. Leverage standards and ensure you are using one data format to connect everything. Have a clear plan based on the objectives of the business and ensure all key players are in alignment. Everything needs to be customized for the client to ensure they receive a good digital, connected experience for customers, partners, and employees.

Cloud, microservices, and more data on more platforms are the most significant drivers affecting change in the integration of applications and data. The proliferation of publicly consumable cloud services with REST and JSON enable you to quickly bring services to market and therefore bring more value to customers more quickly. API middleware is replacing SOAP with RESTful APIs. There’s a proliferation of applications, databases, and interfaces as the amount of unstructured data doubles every 18 months due to IoT and the propensity to hold data in perpetuity.

The technical solution most frequently used to integrate applications and data is open source, though others were mentioned as well. They use open source capabilities that are high in quality and security. Others build their solution on top of JSON and REST for an interface that allows customers to build an integration when, where, and how they want. Although some people claim to have completely proprietary solutions, others believe no one in this day and age is 100% proprietary as the market moves too fast to rely on a single solution.

Real world problems being solved by the integration of applications and data are broad with clients demanding real-time ingestion and analysis to provide real-time solutions including:

• Insurance companies enabling field agents to use mobile devices to issue quotes, see leads, and create scenarios for their clients.

• Reducing the friction of money transfers for mobile banking customers.

• Macadamian working with Phillips Connected Hue Lights to build a connected meeting room that lets people know when the room is occupied or available while managing schedules and calendars.

• A major TV network using real-time KPIs to monitor viewers per show, ad revenue, and monitoring glitches to mitigate revenue loses.

• A portable defibrillator company using their platform to update firmware remotely with traceability to ensure all machines have up-to-date firmware.

• Vinli making non-smart cars smart.

• ParkHub creating a parking platform for large public events which optimizes revenue and reduces shrinkage.

• Robin creating a lawn care application that enables users to manage lawn maintenance from their mobile devices.

• Cisco providing search index optimization.

• Lithium doing product optimization for their community.

• A gaming company offering in-play (a.k.a. “real time”) betting.

• An online mortgage service allowing consumers to be approved for a home mortgage in eight minutes.

• Club Auto in Canada providing an app that enables customers to request a tow truck and see the location of the tow truck as it’s on the way.

Customers expect real-time data from their mobile devices without having to take any action, as well as an Apple-quality user experience.

There are several issues affecting the integration of application and data: the scale and complexity of the data and the applications, service providers over-promising and underdelivering, and demands from inside the company to integrate faster. Data integration is difficult. Companies must bridge the gap between legacy systems and open standards without losing data or risking its security. Customers buy apps and believe they will meet 100% of their requirements out of the box. A lot of companies claim to provide all the needed services with scale and security; however, as the application scales, latency becomes an issue and degrades the user experience. Businesses can’t integrate applications and data quickly enough.

In the future, the integration of data and applications will be more seamless, so “citizen developers” are able to get the information they want. There will be continued growth of data, and the implications thereof will lead to the need for seamless integration. We will move to the citizen as programmer with the cost of entry dropping and the skillset necessary for development getting easier. There will continue to be explosions of endpoints and microservices connected at cloud speed supporting thousands of connections.

Skills that developers need in order to integrate applications and data include knowing how to build APIs, integrate REST endpoints, and JSON. Developers will need to understand why data is important, where it’s going, and the systems it needs to integrate with. Know the types of data to use, how to use it, and how not to be killed by the scale and speed of data. Know the cloud, DevOps, Continuous Integration, and Continuous Development — that’s where the future is.

Stay abreast of what’s new, particularly on the backend of the database. Do not let your knowledge become dated. Be able to see the other person’s perspective.

The majority of companies have, and enforce, API design and management policies. While most companies are using API design and management policies internally, they are using their clients’ standards for APIs.

Virtually all companies are using microservices themselves; however, they’re seeing slow adoption by their clients. Nonetheless, they believe microservices will continue to grow in importance in the future.

Additional considerations were wide-ranging:

• What are the challenges around data sovereignty in an open world?

• Integration is changing from a data exchange to integration with systems that perform like IoT with edge computing.

• Where are people seeing the hybrid cloud going? Will containers change cloud decisions in the modern world? Are people mixing and matching cloud, on-premise, and hybrid data?

• It’s important to look at the expense of the solution relative to the value provided.

• Are people from different organizations structuring data entry for data flow and data in motion? Are there new roles and responsibilities? Centers of excellence have been created in other layers of the data center, should we have this for data flow given the movement of data between nodes?

• Look at open source and proprietary management systems and decide what’s right based on the culture and the nature of the enterprise.

• We aren’t thinking enough about efficiency. We are generating and consuming more data every day, but the network is not growing. How do we keep up? Data is the key component of everything we do. Don’t overlook the infrastructure to capture, store, manage, and analyze.

• The more we move towards a microservices approach, the more important the overall integration strategy to avoid architectural death by a thousand cuts.