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Published inJan 2022
PublisherPackt
ISBN-139781801072137
Edition1st Edition
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Roy Jafari
Roy Jafari
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Roy Jafari

Roy Jafari, Ph.D. is an assistant professor of business analytics at the University of Redlands. Roy has taught and developed college-level courses that cover data cleaning, decision making, data science, machine learning, and optimization. Roy's style of teaching is hands-on and he believes the best way to learn is to learn by doing. He uses active learning teaching philosophy and readers will get to experience active learning in this book. Roy believes that successful data preprocessing only happens when you are equipped with the most efficient tools, have an appropriate understanding of data analytic goals, are aware of data preprocessing steps, and can compare a variety of methods. This belief has shaped the structure of this book.
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Frequent challenges regarding data fusion and integration

While every data integration task is unique, there are a few challenges that you will face frequently. In this chapter, you will learn about those challenges and, through examples, you will pick up the skills to handle them. First, let's learn about each. Then, through examples that feature one or more of them, we will pick up valuable skills to handle them.

Challenge 1 – entity identification

The entity identification challenge – or as it is known in the literature, the entity identification problem – may occur when the data sources are being integrated by adding attributes. The challenge is that the data objects in all the data sources are the same real-world entities with the same definitions of data objects, but they are not easy to connect due to the unique identifiers in the data sources. For instance, in the data integration example section, the sales department and the marketing department...

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Hands-On Data Preprocessing in Python
Published in: Jan 2022Publisher: PacktISBN-13: 9781801072137

Author (1)

author image
Roy Jafari

Roy Jafari, Ph.D. is an assistant professor of business analytics at the University of Redlands. Roy has taught and developed college-level courses that cover data cleaning, decision making, data science, machine learning, and optimization. Roy's style of teaching is hands-on and he believes the best way to learn is to learn by doing. He uses active learning teaching philosophy and readers will get to experience active learning in this book. Roy believes that successful data preprocessing only happens when you are equipped with the most efficient tools, have an appropriate understanding of data analytic goals, are aware of data preprocessing steps, and can compare a variety of methods. This belief has shaped the structure of this book.
Read more about Roy Jafari