2. Books Visualizing Data by Ben Fry Data Structures and Problem Solving Using C++, 2 nd edition by Mark Allen Weiss MATLAB for Engineers, 3 rd edition by Holly Moore

3. Course Outline Introduction to Data Visualization Definition of Data Visualization Importance of Data Visualization Complete Process of Data Visualization Benefits of Data Visualization Quantitative Messages Planning Requirements Interpretation through Data Visualization Interactive Visualization Characteristics of Effective Graphical Display

4. Continued… Data Visualization with C++ Chapter 1 “Arrays, Pointers and Structures” Chapter 2 “Objects and Classes” Chapter 4 “Inheritance” Chapter 6 “Algorithm Analysis” Data Visualization with MATLAB Chapter 2 “MATLAB Environment” Chapter 3 “Built-in MATLAB Functions” Chapter 5 “Plotting” Chapter 6 “User-Defined Functions” Chapter 13 “Numerical Techniques”

5. Data Visualization Data visualization is the presentation of data in a pictorial or graphical format For centuries, people have depended on visual representations such as charts and maps to understand information more easily and quickly As more and more data is collected and analyzed, decision makers at all levels welcome data visualization software that enables them to see analytical results presented visually, find relevance among the millions of variables, communicate concepts and hypotheses to others, and even predict the future

6. Related Terms Data Mining Data Recovery Data Redundancy Data Acquisition Data Validation Data Integrity Data Verification Data Aggregation

7. Data Mining Data Mining is an analytic process designed to explore data in search of consistent patterns and/or systematic relationships between variables Generally, data mining is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both Data mining software is one of a number of analytical tools for analyzing data It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases