new bacon, "data is the new currency and"data is the king " are further stressing the renewed importance of data. But what type of data are we talking about? Obviously, not just any data. The"garbage in garbage out-GIGO concept/principle applies to todays Big Data phenomenon more so than any data definition that we have had in the past to be carefully created/identified, collected, integrated, cleaned, transformed, and ata has To live up to its promise, its value proposition, and its ability to turn into insight, data has properly contextualized for use in accurate and timely decision making. Data is the main heme of this chapter. Accordingly, the chapter starts with a description of the nature of data: what it is, what different types and forms it can come in, and how it can be preprocessed and made ready for analytics. The first few sections of the chapter are dedicated to a deep yet necessary understanding and processing of data. The next few sections describe the statistical methods used to prepare data as input to produce both descriptive and inferential measures. Following the statistics sections are sections or reporting and visualization. A report is a communication artifact prepared with the pecific intention of converting data into information and knowled ge and relaying that information in an easily understandable/digestible format. Nowadays, these reports are more visually oriented, often using colors and graphical icons that collectively look like a dashboard to enhance the information content. Therefore, the latter part of the chapter is ded icated to subsections that present the design, implementation, and best practices for information visualization, storytelling, and information dashboards CHAPTER OUTLINE 2. 1 Opening Vignette: Sirius XM Attracts and Engages a New Generation of Radio Consumers with Data-Driven Marketing 2.2 The Nature of Data 2.3 A Simple Taxonomy of Data 2. 4 The Art and Science of Data Preprocessing 2.5 Statistical Modeling for Business analytics 2.6 Regression Modeling For Inferential Statistics 2.7 Business Reporting 2. 8 Data visualization 2.9 Different Types of Charts and Graphs 2. 10 The Emergence of Visual Analytics 2.11 Information dashboards Copyright C2018 Pearson Education, Inc.2 Copyright © 2018Pearson Education, Inc. new bacon,” “data is the new currency,” and “data is the king” are further stressing the renewed importance of data. But what type of data are we talking about? Obviously, not just any data. The “garbage in garbage out—GIGO” concept/principle applies to today’s “Big Data” phenomenon more so than any data definition that we have had in the past. To live up to its promise, its value proposition, and its ability to turn into insight, data has to be carefully created/identified, collected, integrated, cleaned, transformed, and properly contextualized for use in accurate and timely decision making. Data is the main theme of this chapter. Accordingly, the chapter starts with a description of the nature of data: what it is, what different types and forms it can come in, and how it can be preprocessed and made ready for analytics. The first few sections of the chapter are dedicated to a deep yet necessary understanding and processing of data. The next few sections describe the statistical methods used to prepare data as input to produce both descriptive and inferential measures. Following the statistics sections are sections on reporting and visualization. A report is a communication artifact prepared with the specific intention of converting data into information and knowledge and relaying that information in an easily understandable/digestible format. Nowadays, these reports are more visually oriented, often using colors and graphical icons that collectively look like a dashboard to enhance the information content. Therefore, the latter part of the chapter is dedicated to subsections that present the design, implementation, and best practices for information visualization, storytelling, and information dashboards. CHAPTER OUTLINE 2.1 Opening Vignette: SiriusXM Attracts and Engages a New Generation of Radio Consumers with Data-Driven Marketing 2.2 The Nature of Data 2.3 A Simple Taxonomy of Data 2.4 The Art and Science of Data Preprocessing 2.5 Statistical Modeling for Business Analytics 2.6 Regression Modeling For Inferential Statistics 2.7 Business Reporting 2.8 Data Visualization 2.9 Different Types of Charts and Graphs 2.10 The Emergence of Visual Analytics 2.11 Information Dashboards