| Titre : | Data Analytics and Visualization in Quality Analysis using Tableau |
| Auteurs : | Yoon Youngjin, Auteur ; Hwang Jaejin, Auteur |
| Type de document : | Monographie imprimée |
| Editeur : | CRC Press, 2023 |
| ISBN/ISSN/EAN : | 978-0-367-74416-8 |
| Format : | 1 vol. (210 p.) / ill., couv. ill. en coul / 30 cm |
| Langues: | Anglais |
| Langues originales: | Anglais |
| Index. décimale : | 006.312 |
| Résumé : |
helps quality practitioners perform effective quality control and analysis using Tableau, a user-friendly data analytics and visualization software. It begins with a basic introduction to quality analysis with Tableau including differentiating factors from other platforms. It is followed by a description of features and functions of quality analysis tools followed by step-by-step instructions on how to use Tableau. Further, quality analysis through Tableau based on open source data is explained based on five case studies. Lastly, it systematically describes the implementation of quality analysis through Tableau in an actual workplace via a dashboard example. |
| Sommaire : |
Chapter 1: Introduction
Chapter Abstract Chapter Overview and Expected Learning Outcomes 1.1 Basic Concepts in Quality Analysis 1.2 What is Tableau? 1.3 How to Leverage Tableau in Quality Analysis Chapter 2: Commonly Used Quality Analysis Tools with Tableau Chapter Abstract Chapter Overview and Expected Learning Outcome Tableau Categorizing Fields 2.1 Stacked Bar Chart 2.2 Histogram 2.3 Butterfly Chart 2.4 Donut Chart 2.5 Scatter Plot 2.6 Bubble Chart 2.7 Box Plot 2.8 Pareto Chart 2.9 Bump Chart 2.10 Maps 2.11 Gantt Chart 2.12 Control Chart for Variables 2.13 Control Chart for Attributes Chapter 3: Quality Dashboard Chapter Abstract Chapter Overview and Expected Learning Outcomes 3.1 What is a Dashboard? 3.2 Dashboard Type 3.3 Dashboard Design Approach 3.4 Healthcare Quality Dashboard 3.5 Airline Quality Dashboard 3.6 Manufacturing Quality Dashboard 3.7 Warehouse Quality Dashboard Chapter 4: Case Studies Chapter Abstract Chapter Overview and Expected Learning Outcomes 4.1 Case Studies and Data Storytelling 4.2 Red Wine Quality (Case 1) 4.3 Airline Passenger Satisfaction (Case 2) 4.4 Driverless Car Failure (Case 3) 4.5 Real Time Voice Call Quality Data from Customers (Case 4) 4.6 Brewery Production (Case 5) 4.7 Seoul Bike Sharing Demand (Case 6) |
| Type de document : | Livres |
Disponibilité (1)
| Cote | Support | Localisation | Statut |
|---|---|---|---|
| INF/828 | Livre | bibliothèque sciences exactes | Empruntable |
