There is a new class of clouds on the horizon that are built specifically to handle the big data generated from the Internet of Things (IoT) and its growing offshoot, the Industrial Internet. These IoT clouds integrate that flood of data with real-time analytics to gain greater insight to drive better customer relationships, gain more efficient operations, and improve security and risk management.
Cloud platform and Software-as-a-Service (SaaS) providers IBM and Salesforce.com are both getting into the act, as are multinational enterprises such as General Electric (GE) and multimedia services such as the Weather Company.
Recently, both IBM and GE announced new cloud-based IoT business divisions. According to IBM’s Director for IoT Connectivity and ecosystem, Neil Postlethwaite, “What we want to get to is a consistent view from cloud down to device, from a programming perspective and from a device management perspective.” Not to be outdone, the newly formed GE Digital division is expected to position GE as a “digital show site and grow our software and analytics enterprise from $6B in 2015 to a top 10 software company by 2020,” said Jeffrey Immelt, Chairman and CEO of GE.
And it’s no surprise that SaaS pioneer, Salesforce, is introducing its own brand of IoT cloud. The Salesforce IoT cloud captures device data, as well as data coming from applications, social streams, the Web – basically anything that can help companies build a more complete picture of their customers. According to Dylan Steele, senior director of product marketing for the App Cloud at Salesforce, “When you look behind all of this, there is a customer generating all of this data.”
This new class of cloud is a critical enabler of real-time information services, such as those provided by the Weather Company. By putting IoT data analytics into the cloud, the Weather Company can develop critical weather-based predictive analytics and decision-making resources for individuals, governments and businesses to access on demand. The Weather Company is partnering with IBM Cloud to deliver those forecasts in real-time for 2.2 billion locations across the globe. The president of the Weather Company’s business division, Mark Gildersleeve, said the company is “operating at a scale that we could not have ever imagined prior to the cloud and prior to our ability to bring such computer horsepower to bear.”
At Equinix, we see the cloud as pivotal to the success of the IoT and the Industrial Internet because it’s making larger amounts of big data more accessible to data analytics, faster and more securely. In a recent blog article, we talked about how the cloud is a great place for creating data lakes to access and analyze data. In addition, organizations can directly interconnect with dense cloud ecosystems to alleviate concerns about performance, security, scalability and reliability that can arise when companies have large amounts of data flowing through the public Internet.
Proximate, high-speed connectivity to public cloud services can reduce the amount of latency between data and predictive analytic services, enabling real-time insights into real-world customer preferences, network loads or security risks. Direct interconnection between private data and analytic services within hybrid clouds can avoid the risks associated with public Internet. And automatic access to multiple cloud services via cloud exchanges ensures infinite scalability and redundancy when leveraging an interconnected, multi-regional, multi-cloud environment.
Leveraging the cloud also frees businesses from the high cost of building their own big data analytics IT infrastructures. According to a 2014 ESG report, “Getting Real about Big Data: Build vs. Buy,” the three-year total cost of ownership of a single, medium big data “build” is estimated to be $920,900.
When looking to fully leverage cloud-based big data storage and analytics services, look for globally distributed colocation and interconnection data centers that can access multiple cloud services directly and securely using fast, private connections, with unlimited scalability and reliability capabilities.