Data Quality Fundamentals
Autor Barr Moses, Lior Gavish, Molly Vorwercken Limba Engleză Paperback – 15 sep 2022
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Specificații
ISBN-13: 9781098112042
ISBN-10: 1098112040
Pagini: 300
Dimensiuni: 177 x 237 x 17 mm
Greutate: 0.52 kg
Editura: O'Reilly
ISBN-10: 1098112040
Pagini: 300
Dimensiuni: 177 x 237 x 17 mm
Greutate: 0.52 kg
Editura: O'Reilly
Notă biografică
Barr Moses is the CEO and co-founder of Monte Carlo, a data reliability company. In her decade-long career in data, Barr has served as commander of a data intelligence unit in the Israeli Air Force, a consultant at Bain & Company, and VP of Operations at Gainsight, where she built and led their data and analytics team. The instructor of O'Reilly first course on Data Observability, an emerging discipline in data engineering, Barr has worked with hundreds of data teams struggling with these problems. Inspired by her time in the analytics trenches, she is building a product literally dedicated to identifying, resolving, and preventing what she calls "data downtime," periods of time when data is missing, erroneous, or otherwise inaccurate. In other words: bad data. In this book, she shares her experiences and learnings on how today's data organizations can achieve high data quality at scale through technological, organization, and cultural best practices.