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The Harvard Startup Disrupting Big Data and the Internet of Things
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August 11, 2016 News

For a company to succeed, it is essential that their practices are data-driven. For many companies, that means harnessing insights from Big Data. Addressing this issue head-on is Harvard-incubated Experfy. Cofounded by Harpreet Singh and Sarabjot Kaur, Experfy has built a vetted marketplace for data and Internet of Thigns consulting and training to help companies derive the actionable insights from Big Data that they need to be successful.

Inaccessibility to Big Data and Internet of Things Expertise

Big Data – the term used to refer to large data sets that are too complex for ordinary data processing systems to manage – is becoming an increasingly important aspect of business and innovation across the globe.  For many companies, having effective tools to reveal trends and associations with sets of data is crucial. The Internet of Things (IoT) refers to tens of millions of devices connected to the Internet that are generating massive amounts of data.

Unfortunately, getting access to Big Data and IoT expertise isn’t always easy or cost effective for companies to do. According to McKinsey Global Institute, “[b]y 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.”

A “McKinsey[…]for Big Data Consulting”

TechCrunch calls Experfy a “McKinsey in the cloud for big data consulting” and Datanami calls it the “Uber of big-data projects.”  With over 25,000 data experts, Experfy is now the world’s largest Big Data and IoT consulting marketplace.

How have they been able to scale so quickly? By providing value.

For its training platform, the company has developed courses on IoT, Big Data, security, cloud, and emerging technologies (like augmented reality and blockchain) for beginners and experts alike. There are also short courses on topics such as monetizing big data for executives, as well as industry courses on Big Data use-cases in healthcare, financial services and market research. This type of domain-specific offering in this industry is the first of its kind, and has enabled many companies to reap the benefits from data which otherwise would have gone unrecognized.

Marketplace for Big Data and IoT Professionals

While there are other training sites available, the mapping of courses to real projects is one unique element that enables Experfy to stand out from the pack.

Growing out of the Harvard Innovation Lab, Experfy has found new opportunity in Big Data consulting by transforming large quantities of data into actionable insights, and offering custom algorithms on demand.

How does their market place actually work? It provides a communal space for data scientists, individuals, and businesses to collaborate on Big Data and IoT projects, providing value to both parties.

Lots has happened for Experfy since the company was founded in 2014. Their user base has grown not only in quantity, but also in quality. Industry thought leaders from Harvard, Amazon, Apple and other top companies are now on the Experfy platform, as well as academic institutions like Harvard, MIT and Columbia. They are launching with 50 courses and have another 100 in the pipeline, planning to engage even more high profile users.

More Importantly: An Education Platform

In the grand scheme of things, however, Experfy isn’t just any Big Data company. They consistently provide real world projects to their students through their consulting marketplace, with the vision of offering courses that address every industry need by creating learning paths from Retail and Healthcare to Insurance and Telecom. All of this occurs in the context of a highly scalable platform where any instructor can sign-up, be vetted, and then produce a course using our high standards.

In the future, Experfy will continue to grow though leadership and close the gap between big data and actionable insights.

 This article was originally published on tech.co and can be viewed in full

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