We also decided against leveraging a search infrastructure like Galene (Lucene-based index), as it was better suited for matching entities and ranking based on relevance scores than for aggregating metrics. To help illustrate, if you wanted to compute a metric for all the possible combinations when picking 10 skills from the LinkedIn skills taxonomy of 36K skills, you would produce a dataset of 1.0062805 x 10 39 records! We realized it was not scalable to precompute metrics, given the astronomical number of combinations of search dimensions across skills, titles, locations, industries, and functions.
#Linkedin talent insights software
Through mapping every member, company, job, and school, Talent Insights can help users answer questions like: What is the fastest growing skill in the software industry? Which schools did company X’s employees graduate from? Which companies is company X losing its talent to? Users can further explore the data by filtering on various dimensions like geographic locations, member skills, member titles, and years of experience. The Economic Graph consists of 690 million members, 36,000 skills, 50 million companies, and 90,000 schools. Talent Insights accomplishes this by providing unparalleled access to LinkedIn’s Economic Graph, providing metrics that allow its users to make data-driven decisions in developing their talent strategy. This is a tool that helps organizations understand the external labor market, their internal workforce, and enable the long term success of their employees. One way we’ve worked toward this goal is through LinkedIn Talent Insights, which first launched in 2018.
LinkedIn is a mission-driven organization, and we take our mission of “connecting the world's professionals to make them more productive and successful” very seriously. Co-authors: Timothy Santos and Jeremy Lwanga
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