Wu Jiye: How LinkedIn uses large data to achieve business value

The first China cloud Computing conference was opened in June 2013 5-7th at the Beijing National Convention Center. The Conference, with an international perspective, insights into global cloud computing trends, and from the application, explore cloud computing and large data, cloud computing and mobile Internet, cloud security and cloud computing industry applications, such as the focus of the topic. In particular, the Conference has set up a cloud computing services display area, exchange the latest research results of international cloud computing, showcase domestic cloud computing pilot City development achievements, share cloud computing development experience, promote global cloud computing innovation cooperation.

In the Forum on core technology architecture for cloud computing, Wu Jiye, the technical head of the data analysis solution for the LinkedIn Business Analytics team, describes how the LinkedIn Business Analytics Department supports the product design and strategic planning of the company's business through data services.

Figure: Wu Jiye, technical head of the data analysis solution for the LinkedIn Business Analytics team

Wu Jiye says LinkedIn has always been focused on the interests of its members, respecting and protecting the privacy of its users.

The LinkedIn Business Analytics team was founded in 2011, from 4 to now more than 50 people, including three business Analytics teams vertically supporting LinkedIn's three business solutions, talent solutions, market solutions, and personal advanced subscription services; and a focus on data integration, The data presentation team and a dedicated data mining team support three business analysis teams horizontally.

Wu Jiye said that LinkedIn's three major business solutions were lucrative for the company, which includes talent solutions, market solutions and advanced subscription services.

Figure: LinkedIn Data tools

Wu Jiye, the LinkedIn Business Analytics department uses a large number of open source and commercial software to build a powerful database of data tools.

Figure: LinkedIn Data flow

The LinkedIn Business Analytics Division divides the data into online, near-line, and offline data. Oracle Espresso, Teradata Hadoop data warehouses, and open source Voldemort databases support LinkedIn's data analysis platform.

(Responsible editor: Lu Guang)