Principles of Data Wrangling: Practical Techniques for Data Preparation
| Author | : | |
| Rating | : | 4.67 (523 Votes) |
| Asin | : | B073HMH8XG |
| Format Type | : | |
| Number of Pages | : | 434 Pages |
| Publish Date | : | 2015-09-11 |
| Language | : | English |
DESCRIPTION:
You’ll learn a shared language and a comprehensive understanding of data wrangling, with an emphasis on recent agile analytic processes used by many of today’s data-driven organizations.Appreciate the importance—and the satisfaction—of wrangling data the right way.Understand what kind of data is availableChoose which data to use and at what level of detailMeaningfully combine multiple sources of dataDecide how to distill the results to a size and shape that can drive downstream analysis. Written by key executives at Trifacta, this book walks you through the wrangling process by exploring several factors—time, granularity, scope, and structure—that you need to consider as you begin to work with data. A key task that any aspiring data-driven organization needs to learn is data wrangling, the process of converting raw data into something truly useful. This practical guide provides business analysts with an overview of various data wrangling techniques and tools, and puts the practice of data wrangling into context by asking, "W
Prior to Trifacta, he was a Data Scientist at Facebook and the Director of Data Science Strategy at R/GA.. He holds a Ph.D. About the AuthorTye Rattenbury is Trifacta's lead data scientist. in Computer Science from UC Berkeley
in Computer Science from UC Berkeley. He holds a Ph.D. Tye Rattenbury is Trifacta's lead data scientist. Prior to Trifacta, he was a Data Scientist at Facebook and the Director of Data Science Strategy at R/GA.