Digital companies are increasingly building intelligent systems (software and devices) to offer improved digital self-service experiences, robotically automate operations, and augment decision-making with intelligent recommendations and actions. One thing common in these new age systems is that they are using intelligent analytics powered by augmented / artificial intelligence.
What is intelligent analytics?
Intelligent Analytics refers to Analytics that leverages augmented / artificial intelligence techniques such as natural language processing, logical reasoning, machine learning, machine vision, pattern recognition and cognitive computing to support capabilities needed by intelligent systems to learn, solve problems, and augment human decision making i.e. Analytics for Intelligent Systems.
The combination of intelligent analytics with bots, intelligent agents & apps, and robotic process automation (software robots) are helping solve problems, find new efficiencies, and enhance experiences.
Intelligent Apps combine customer, product and operational insights (uncovered with Intelligent Analytics) with new application development tools & capabilities and focus on user-centric design to create a more compelling, more prescriptive user experience. These intelligent apps not only know how to augment key user decisions, but they continually learn & adapt from the user interactions to become even more relevant and valuable to those users.
Intelligent automation systems sense and synthesize vast amounts of information and automate entire processes or workflows, learning and adapting as they go. They are chunks of software code combining automation with intelligence analytics (driven on data we already have) to create finely tuned models that intelligently prioritize and route tasks, reduce costs dramatically and speed time‑to‑resolution.
While early IoT applications were mostly about collecting data from IoT devices and sending them somewhere else for analysis, edge computing is focused on building advanced analytics, machine learning and artificial intelligence in the cloud and deploying to intelligent devices at the edge. You get the best of both worlds with intelligent devices that can act locally based on the data they generate, while also taking advantage of the cloud to configure, deploy, and manage them securely and at scale.
Why cloud-first for intelligent analytics?
We believe Cloud to be a strategic and foundational enabler for building intelligent analytics. The Cloud provides a continuum of building-blocks and cutting-edge development tools necessary for experimenting and building intelligent analytics and systems.
With a cloud-first strategy organizations focused on intelligent analytics & systems:
- Get access to latest analytics capabilities
- Accelerate software delivery using the latest intelligent app, automation, & device development tools
- Lower startup cost and investment risk for innovation
- Achieve on-demand and rapid resource elasticity as operations scale
- Manage resources cost effectively
- Maintain higher reliability and security at scale