Case Study:
eBay Moves to Self-Service Data Discovery
Online retailers are bursting with data. From items that customers add to their online carts to inventory in warehouses, there’s virtually no limit to data available for analysis. Since they cannot observe their customers, online retailers depend on logs recording detailed web site activity of visitors, including what links were clicked and how long a visitor remained on a webpage. eBay Moves to Self-Service Data Discovery With more than 97 million active users globally, eBay is the world’s largest online marketplace where just about anything can be bought or sold—and an immense volume of data. eBay collects more than 5 terabytes (TB) of data every day, and the insight they need to run the business is in that data. At eBay, the trend is toward making sure everyone in the organization can do their own data discovery. David Stone, SeniorManager Analytics Platform at eBay, described the importance of offering data analytics tools to members of the eBay team. Stone explained: When limited to Excel and its million-row limit, it caused us to look at the top three categories instead of the top 40,000 categories and there’s so much less data. At eBay that’s important because there is more action out in the long tail accumulated than there is in the top three. Using data discovery software, eBay can dig deep into items in their top 40,000 categories because they no longer face row limits. Employees can now interact and visualize data, and can do data discovery on their own to better manage performance.
Q1. In what way is data discovery more critical to online retailers than to retailers with physical stores?
Q2. How did Excel limit eBay’s data analysis?
Q3. Discuss the impacts of self-service data discovery on eBay.
Q4. Research the following: How large is a terabyte (TB)?
Your answer must be typed, double-spaced, Times New Roman font (size 12), one-inch margins on all sides, APA format and also include references.