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Mastering Tableau

You're reading from   Mastering Tableau Smart Business Intelligence techniques to get maximum insights from your data

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Product type Paperback
Published in Dec 2016
Publisher Packt
ISBN-13 9781784397692
Length 476 pages
Edition 1st Edition
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Authors (2):
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Jen Stirrup Jen Stirrup
Author Profile Icon Jen Stirrup
Jen Stirrup
David Baldwin David Baldwin
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David Baldwin
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Toc

Table of Contents (14) Chapters Close

Preface 1. Getting Up to Speed – a Review of the Basics FREE CHAPTER 2. All about Data – Getting Your Data Ready 3. All about Data – Joins, Blends, and Data Structures 4. All about Data – Data Densification, Cubes, and Big Data 5. Table Calculations 6. Level of Detail Calculations 7. Beyond the Basic Chart Types 8. Mapping 9. Tableau for Presentations 10. Visualization Best Practices and Dashboard Design 11. Improving Performance 12. Interacting with Tableau Server 13. R Integration

Data-mining and knowledge-discovery process models

Data modeling, data preparation, database design, data architecture; how do these and other, similar terms fit together? This is no easy question to answer! Terms may be used interchangeably in some contexts and be quite distinct in others. Also, understanding the interconnectivity of any technical jargon can be challenging. In the data world, data mining and knowledge-discovery process models attempt to consistently define terms and contextually position and define the various data sub-disciplines. Since the early 1990s, various models have been proposed. The following list is adapted from A Survey of Knowledge Discovery and Data Mining Process Models by Lukasz A. Kurgan and Petr Musilek, published in The Knowledge Engineering Review Volume 21 Issue 1, March 2006.

Survey of the process models

Fayyad et al.

KDD

CRISP-DM

Cios et al

SEMMA

Developing and Understanding of the Application Domain

Selection

Business Understanding...

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