Building a Successful Enterprise-Grade IoT Platform

IoT connected devices are turning up everywhere. Every major communications carrier is offering its own IoT platform. And hundreds of technology companies are offering capabilities for IoT use case implementation. But the crux of the matter is not what options there are, but how to make it all work together. What’s needed is a common framework for creating true value — a way to make everything work together — essentially an integrated data plane, connecting scalable compute and storage and big data analytics.

This blog highlights how to enable the initial deployment and subsequent growth needs for any enterprise starting to making an IoT investment. Organizations making this investment will see expected returns in several categories, including additional revenue, optimization of operations, significantly improved experiences, and stronger customer loyalty.

As a company, we are seeing IoT projects in every industry and government sector. Both public and private companies are preparing project budgets and including IoT as a major item in their planning cycles. For example, here at Hortonworks, we are seeing:

• Auto insurance customers issue Smart Auto Policies using usage-based insurance through an in-car sensor that transmits IoT driving data.  
• Digital marketing customers processing and storing billions of online events a day to predict optimal online ad placements.  
• Security customers monitoring millions of users and 100s of millions of IoT devices in real time.  

The right IoT platform capabilities must be in place to support these demanding IoT implementation needs. So what does it take to implement a successful IoT platform? Let’s list the high-level requirements for successful enterprise-grade IoT platform:

• Must be able to manage a vast array of connected devices
  • Includes sensors, meters, mobile devices, machines and other “Things.”
• Must offer secure network connectivity
  • For initial device discovery and also for subsequent re-establishment of dropped links.
• Must provide a “Data Plane of Control”
  • From far edge devices to regional and centralized data centers to meet regulatory and audit requirements.
• Must offer a “Scalable Compute and Storage” architecture
  • To process and subsequently store a high velocity, variety and volume of data.
• Must provide “Big Data Analytics”
  • Support of closed loop analytics is required to garner the business benefits and operational efficiencies of any IoT implementation         

Today, Hortonworks offers “Data Plane of Control”, “Scalable Compute and Storage” and “Big Data Analytics” though Hortonworks Data Flow (HDF) and the Hortonworks Data Platform (HDP).  

• To support the “Data Plane of Control,” Hortonworks offers HDF –  an enterprise ready platform for data in motion. HDF 2.0 is now available and has been extended to reach intelligent far edge devices by offering for the first time — MiNiFI as well as client libraries.  
• To support “Scalable Compute and Storage,” Hortonworks offers HDP, powered by core Apache Hadoop, containing YARN, and HDFS.
• And for “Big Data Analytics”, Hortonworks offers Apache Storm (for real-time event stream processing) and Apache Spark (for Advanced Analytics, including machine learning).  

The other must-haves are managing a vast array of connected devices and the ability to offer secure network connectivity working in tandem with such an ecosystem. Forward-thinking organizations are turning to IoT to drive additional revenue, improve operational efficiencies, and increase customer satisfaction and loyalty.