With its acquisition of online learning site Lynda.com, LinkedIn will have a hand in creating opportunities among professionals who are interested in acquiring new skills.
The insight it gains into people's training will make LinkedIn more valuable to companies as a way to assess potential hires. And it will become more valuable for technically oriented professionals who wish to market themselves to potential employers.
The acquisition looks to be well-timed, given that e-learning has attracted several billion in venture capital over the past five years and that many VCs believe the education market is ripe for disruption.
LinkedIn said on Thursday that it has agreed to acquire Lynda.com for $1.5 billion in cash and stock. Jeff Weiner, CEO of LinkedIn, said in a statement that the missions of the two companies are closely aligned. LinkedIn, the leading professional social network, has around 350 million members, who use the site for group-based interaction, professional networking, and job searches. Lynda.com offers online training for job-related skills.
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"Skills is one of the final pieces of the puzzle," Weiner explained in a video about the deal. "It's not enough to standardize the data around the skills required to obtain a role. It's also important that we can actually help people obtain those skills themselves."
LinkedIn demonstrated its interest in capturing skill data in 2013, when it partnered with Coursera, EdX, lynda.com, Pearson, Skillsoft, Udacity, and Udemy to display course completion certificates in LinkedIn profiles.
In a blog post, Weiner described LinkedIn's fundamental value proposition as connecting people and opportunity. Key to Weiner's vision of connection is what he called the Economic Graph, which is really just a way of describing relationships among data sets. Just as Facebook's Social Graph represents the way that its users are connected, LinkedIn wants to create an Economic Graph that connects employers, employees, skills, and opportunities.
LinkedIn began rolling out the infrastructure to support its Economic Graph last year when it introduced its Galene search architecture to overcome the limitations of Lucene-based system. Among other things, the architectural change allowed LinkedIn to provide Instant Member Search beyond second-degree connections, with improved relevance, at twice the speed.
Galene will allow searches where the search terms are not present in the entities searched, but may exist at the edges of the Economic Graph. An example of this sort of search could be something like, "Data science jobs in New York in companies where my connections have worked," suggested LinkedIn engineer Sriram Sankar in a blog post last year.
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