Book Image

Mastering Tableau 2021 - Third Edition

By : Marleen Meier, David Baldwin
Book Image

Mastering Tableau 2021 - Third Edition

By: Marleen Meier, David Baldwin

Overview of this book

Tableau is one of the leading business intelligence (BI) tools that can help you solve data analysis challenges. With this book, you will master Tableau's features and offerings in various paradigms of the BI domain. Updated with fresh topics including Quick Level of Detail expressions, the newest Tableau Server features, Einstein Discovery, and more, this book covers essential Tableau concepts and advanced functionalities. Leveraging Tableau Hyper files and using Prep Builder, you’ll be able to perform data preparation and handling easily. You’ll gear up to perform complex joins, spatial joins, unions, and data blending tasks using practical examples. Next, you’ll learn how to execute data densification and further explore expert-level examples to help you with calculations, mapping, and visual design using Tableau extensions. You’ll also learn about improving dashboard performance, connecting to Tableau Server and understanding data visualization with examples. Finally, you'll cover advanced use cases such as self-service analysis, time series analysis, and geo-spatial analysis, and connect Tableau to Python and R to implement programming functionalities within it. By the end of this Tableau book, you’ll have mastered the advanced offerings of Tableau 2021 and be able to tackle common and advanced challenges in the BI domain.
Table of Contents (18 chapters)
16
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17
Index

Tableau and big data

Perhaps the first challenge of big data is defining it adequately. It's a term so widely used as to be almost meaningless. For example, some may refer to data exceeding 1,048,576 rows as big data (which is the row limit in Excel 2010 and 2013) while others would only apply the term to datasets in the multiple petabyte range. Definitions found on Wikipedia (https://en.wikipedia.org/wiki/Big_data) and Webopedia (https://www.webopedia.com/TERM/B/big_data.html) are so broad as to encompass both of these examples. True, it is probably simplistic to consider data that merely exceeds Excel's row limitation as big data; nevertheless, from the perspective of an individual for whom Excel is the traditional data-processing application, the preceding definitions fit.

Rather than try to provide an adequately narrow definition of what is essentially a buzzword, this section will primarily focus on one aspect of big data: massively parallel processing. However...