Data visualization. / Volume 1, : Recent trends and applications using conventional and big data / / Amar Sahay.

• Superior document: Quantitative approaches to decision making collection,
• VerfasserIn: Sahay, Amar,
• Place / Publishing House: New York, New York (222 East 46th Street, New York, NY 10017) : : Business Expert Press,, 2017.
• Year of Publication: 2017
• Edition: First edition.
• Language: English
• Series: Quantitative approaches to decision making collection.
• Physical Description: 1 online resource (xii, 180 pages)

Data visualization involves graphical and visual tools used in data analysis and decision making. The emphasis in this book is on recent trends and applications of visualization tools using conventional and big data. These tools are widely used in data visualization and quality improvement to analyze, enhance, and improve the quality of products and services. Data visualization is an easy way to obtain a first look at the data visually. The book provides a collection of visual and graphical tools widely used to gain an insight into the data before applying more complex analysis. The focus is on the key application areas of these tools including business process improvement, business data analysis, health care, finance, manufacturing, engineering, process improvement, and Lean Six Sigma. The key areas of application include data and data analysis concepts, recent trends in data visualization and "Big Data," widely used charts and graphs and their applications, analysis of the relationships between two or more variables graphically using scatterplots, bubble graphs, matrix plots, etc., data visualization with big data, computer applications and implementation of widely used graphical and visual tools, and computer instructions to create the graphics presented along with the data files.

Table of Contents

Graphical and visual tools for improving business process, product, and service quality -- 1. Overview and importance of visual representation -- 2. Data and data analysis concepts -- 3. Visual representation of data -- 4. Exploring relationships between two or more variables graphically -- 5. Data visualization with big data -- 6. Computer applications and implementation -- Appendix A. Charts and graphs using EXCEL -- Appendix B. Pivot table applications in descriptive statistics and data analysis -- Appendix C. Charts and graphs using MINITAB 17 -- Bibliography -- Index.