In today’s world of automated data collection, manufacturers are looking for solutions that can process and analyze their mountains of shop-floor data and provide useful, actionable information. These companies want quick answers to all of their major quality problems and process improvement initiatives. What sites need the most attention? What lines generate the most quality issues? What products produce the highest levels of scrap? Are there certain features causing problems on an entire product line? Where is the low-hanging fruit or easy improvement opportunities? This session will discuss new ways of analyzing huge amounts of data, while still adhering to sound statistical principles. It will cover data organization, yield computations, grading, and roll-up techniques. Attendees will learn how to get instant insight out of their current big data repositories.