When LinkedIn was launched in 2003, it took them 500 days to reach their first million customers; the most recent million took just six days. Today there are two new registrations with the site every second, 4.2 billion user searches a year and the data analysis team looks at 200 TB of data each day to understand its users better.
Five years ago, inWhat is Web 2.0, Tim O’Reilly said that “data is the next Intel Inside.” Why do we suddenly care about statistics and about data? Why data science is the Sexiest Job of the 21st Century? This Lesson focus on getting some of the answers from Manu Sharma
LinkedIn is your professional digital real estate. When people look for you and don’t find you it’s like lose of a potential opportunity. Therefore it’s important to keep the profile up-to-date. LinkedIn uses data to build products and generate insights to drive the business. To achieve this LinkedIn have developed proprietary algorithms such as Metropolis. It process over 10 billion rows of data everyday in real time by building it’s own unique solutions like Voldemort, Kafka, Zoie. These have been made open source now.
Data Scientist is the right combination of curiosity and intuition; I wonder what can I do with this data? what questions can I ask? What can this data tell me? It’s about having the right intuition to know the limitations of your approaches. It involves gathering data, standardizing it, doing the right modeling, doing stacks on it and having the ability to code it. A data scientist needs all these skills and that’s what startups should look for when setting up their data science teams.