I have seen the future! Of course, I seem to say that every other month (maybe that’s because the future keeps changing?), but this is a good one. The future is a collision between big data (and data science) and application development that will yield a world of “intelligent apps.” These “intelligent apps” combine customer, product and operational insights (uncovered with predictive and prescriptive analytics) with modern application development tools and user-centric design to create a more compelling, more prescriptive user experience. These intelligent apps not only know how to support or enable key user decisions, but they continually learn from the user interactions to become even more relevant and valuable to those users.
Several developments and posts by industry leaders over the past few weeks have started to add some substance to this intelligent apps trend, including:
In particular, I like the IDC research that states “by 2018, more than half of the teams developing apps will embed some kind of cognitive services in them, up from 1% in 2015.” That is an unprecedented growth and transformation rate.
The chart below summarizes the market opportunity with the integration of IOT apps and IOT analytics to create intelligent IOT apps (see Figure 1).
All of this research and market activity is consistent with the conversations that I am having with customers, who are trying to determine how best to deliver their customer, product and operational analytics in an actionable way that can optimize key business processes, uncover new monetization opportunities, and create a more compelling customer and partner engagement.
The path to building intelligent applications starts by understanding the decisions that key business constituents need to make in support their business and operational objectives. Decisions are key because it is around these decisions that we will leverage the ever-growing wealth of internal and publicly available data (e.g., transactional, social, web, mobile, wearables, sensors, embedded, bionic) with data science (e.g., predictive analytics, machine learning, data mining, cognitive computing) to optimize those decisions. That is an approach that we embrace in guiding our clients through their digital business transformation with our Big Data Vision Workshop, Proof of Value and Operationalize offerings (see Figure 2).
To create intelligent applications, organizations will need to embrace key application technology and architecture capabilities including:
Data Lake that supports:
Data as a Service that supports:
Analytics as a Service (Enterprise Analytics) that supports:
Intelligent Applications (App Development) that supports:
Figure 3 summarizes the key capabilities and functionalities necessary to build intelligent applications (special thanks to Clark Christensen for Figure 3).
Let’s be honest, it only makes logical sense to integrate analytics with application development to create intelligent apps that not only deliver a more compelling user experience, but also learn from the user engagement to become more relevant and important to those users. I mean, why collect all this transactional, social, mobile, wearable and IOT data if you aren’t going to do something with it. And the most logical way to drive action (optimized operational decisions) from the data and analytics is via intelligent applications.