Speakers: Jonathan Wu (LinkedIn), Praveen Neppalli Naga (LinkedIn), Chi-Yi Kuan (LinkedIn) Category: Hadoop in Action LinkedIn processes enormous amounts of events each day. This data is of critical importance for data analysts, engineers, business experts, and data scientists that seek deep understanding of the interactions within LinkedIn’s professional social graph. They use this data to derive insights and performance metrics, which lead to better business decisions on products, marketing, sales, and other functional areas. Areas of interest include Email, Growth, Engagement, and Trending metrics. Development of internal tools has traditionally been based on specific need, optimized for the business use case, and non-interoperable. The engineering challenge is to allow business users to easily access and organize huge amounts of data in a comprehensive way and to be able to flexible and quickly get to the insights through graphs and charts that they need. The data needs to be sufficiently granular to work for different needs, the interface needs to be intuitive and simple, and the infrastructure needs to be high performance allowing users to manipulate large amounts of data quickly. The solution to this challenge was realized by the LinkedIn Business Analytics and Data Analytics Infrastructure teams utilizing an integrated stack that includes an interactive analytics infrastructure and a self-serve data visualization front-end solution. The user interface provides a customizable ability to build charts, tables, and queries to suit highly customized reporting needs on any devices. The back-end infrastructure is based on Hadoop; which leverages LinkedIn’s investment in high scalable, data rich systems. The combined solution brings the ability to visualize, slice, dice, and drill through billions of records and hundreds of dimensions at fast scale. In this talk, you will learn the background of the data challenges that LinkedIn faced, how the teams came together to construct the solution, and the underlying stack structure powering this solution.