Since 2017, Dr. Baeza-Yates is also part-time director of data science programs in Northeastern University at the Bay Area. Before, Dr. Baeza-Yates was VP of Research at Yahoo Labs from 2006 to 2016. He obtained a Ph.D. in CS from University of Waterloo, Canada, in 1989. Dr. Baeza-Yates is co-author of the best-seller Modern Information Retrieval textbook, that won the ASIST 2012 Book of the Year award. He has been member of the ACM Council and the Board of the IEEE Computer Society. Dr. Baeza-Yates is an ACM & IEEE Fellow.
Challenges of {BIG, small, Right} Data
Big data is trendy, but there are many possible interpretations of its real impact, as well as the opportunities, risks and technological challenges. We will start with two key questions: can a company use big data? If so, should it? The opportunities are clear, while the challenges are many, including scalability, bias, and privacy on the problem side, as well as transparency, explainability, and ethics on the machine learning side. So we perform an analysis that includes all the data pipeline process. At the end we will conclude that what is important is the right data, not big data. In fact, the real challenge today, is machine learning for small data.
