This page requires that JavaScript be enabled in your browser.
Learn how »
Working with Dirty Data: To Cleanse or Not to Cleanse... and How to Decide
Nicholas Marko, Dr. Oleg Roderick
Nicholas Marko and Oleg Roderick address the issue of using incomplete, damaged, incorrectly interpreted, and otherwise “dirty” data in modern analytics, and use their experiences in healthcare as a baseline from which to discuss this universal challenge in data science.
Thanks for your feedback.
Channels: Data Summit
69 videos match your search.
 |
Clark Freifeld Together, HealthMap and MedWatcher demonstrate the power of internet media to improve public health. |
 |
Christian Herzog In this talk, concrete examples from our partners on portfolio alignment, reporting, and process support leveraging the global award database are shared. |
 |
Chris Rezendes Conversations about value and benefits in IoT tend to fall into one of two loose buckets: some level of specificity relating to brands/OEMs and their customers, or high-level concepts ... |
 |
Boe Hartman We have developed in-house a social monitoring platform that uses rule-based models to determine from data dark what kind of customer experience we are passing onto our customer base across ... |
 |
Ben Vershbow Ben Vershbow walks through The New York Public Library’s experiments in digitizing historical maps, showing how they can be processed (with the help of computers and crowds) into open ... |
 |
Anthony Scriffignano This session discusses some of the critical evolutions in the discovery and curation of relationships involving business entities and people in the context of those entities on a global scale, ... |
 |
Anita de Waard The main tenet of the current "data science" trend is that new science can be done on old data. To make this possible, the data needs to be collected and ... |
 |
Amanda Welsh Wolfram's 5th Annual Data Summit is a high-level gathering of innovators in data science, creators of connected devices, and leaders of major data repositories. |
 |
Aditya Khosla While prior work in computer vision has focused on what is in the image, in this talk, we leverage big data to look beyond the simple visual elements to develop ... |
