The Commercialization of Analytics : A Vital Thread in the Internet of Things Movement
As more things connect to the Internet, petabytes of data are being generated. These huge amounts of data don’t mean much in the business world, however, unless this information is dissected to its core and analyzed as to how it can affect specific industries.
Take for example a recent statement by Wikibon Principal Analyst Jeff Kelly regarding Industrial Internet Big Data in his report “The Industrial Internet and Big Data Analytics: Opportunities and Challenges,” where he emphasizes that tools and technologies used to process, store, analyze, and optimize Industrial Internet Big Data vary per industry, depending on the mission-critical nature of the workloads.
“[C]onsider the impact of administering the wrong medication to a critically ill patient versus serving up the wrong display ad to someone browsing the Internet. Or the consequences of engine failure on an airliner 30,000 feet over the Pacific Ocean versus an online shopping application crashing during checkout. In both cases, the potential value and consequences of the former dwarf those of the latter,” Kelly explained.
But how has analytics found its way into mainstream?
A brief history of the commercialization of analytics
The commercialization of analytics began in the 1950s when ENIAC, the first electronic general-purpose computer, generated the first model that predicts weather forecast. In 1956, analytics was used to solve the “shortest path problem” and it improved air travel and logistics. In 1958, FICO applied predictive modeling to credit risk decisions.
The use of analytics boomed, crossing over into the mainstream in the 1970s in a trend that continued until 2000, when analytics was proven to be an important part of various industries.
A number of milestones in analytics happened in the 1970s up to the present, such as the creation of the Black-Scholes model to predict optimal price for stock options over time, the first commercial tool for building a model-driven Decision Support System was marketed and FICO deployed real-time analytics to prevent credit card fraud.
There was also the birth of Amazon and eBay, as well as Google, all using analytics to deliver more relevant recommendations and search results. And with the emergence of a more social community, analytics is being applied to a range of consumer recommendation services, suggesting films, restaurants and countless retail items.
To learn more how analytics evolved over time, check out the infographic below:
Tech giants commercializing analytics for tomorrow
Giants in the industry have also taken analytics a step further. As mentioned above, the Industrial Internet, as well as the Internet of Things, are growing as more devices are being connected to the internet and its subsequent data gets analyzed.
GE is at the forefront of the Industrial Internet, as it recently released its industrial strength Big Data and analytics platform, expanded its partnerships with Accenture, Pivotal and Amazon Web Services, and hires thousands of engineers as it moves to connect everything to the Internet, from jet engines, wind turbines, MRI machines, locomotives and other industrial grade equipment.
IBM is highly invested in analytics as well, and its using it to help people get better medical care with Watson. At the recent IBM Edge event, it was announced that Watson is being used to aid in the treatment of lung and breast cancer at the Memorial Sloan-Kettering Cancer Center, as well as streamlining treatment preauthorizations at WellPoint. This makes obtaining treatment preauthorization shorter, which in turn makes the whole treatment process less expensive, enabling patients to more consistently receive gets the best medical care.
And HP is also a big investor in analytics. The company’s Business Service Management team is focused on Advanced Analytics, which includes tools for data visualization. After all, seeing the data is much easier than using your imagination.
Analytics is a huge part of our lives even if we don’t know or realize it. The apps recommended to us, the movies we should watch, the places we should visit – these are the just some of the commercial areas where analytics play a huge role. In all, Big Data, the Internet of Things and the Industrial Internet would not be possible without analytics.
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