大数据导论（英文版） PDF下载

Contents
PART I: THE FUNDAMENTALS OF BIG DATA
CHAPTER 1: Understanding Big Data 3
Concepts and Terminology 5
Datasets 5
Data Analysis 6
Data Analytics 6
Descriptive Analytics 8
Diagnostic Analytics 9
Predictive Analytics 10
Prescriptive Analytics 11
Business Intelligence (BI) 12
Key Performance Indicators (KPI) 12
Big Data Characteristics 13Contents<；br>；PART I: THE FUNDAMENTALS OF BIG DATA<；br>；CHAPTER 1: Understanding Big Data                    3<；br>；Concepts and Terminology                              5<；br>；Datasets                                             5<；br>；Data Analysis                                          6<；br>；Data Analytics                                          6<；br>；Descriptive Analytics                                       8<；br>；Diagnostic Analytics                                         9<；br>；Predictive Analytics                                       10<；br>；Prescriptive Analytics                                        11<；br>；Business Intelligence (BI)                               12<；br>；Key Performance Indicators (KPI)                          12<；br>；Big Data Characteristics                               13<；br>；Volume                                               14<；br>；Velocity                                             14<；br>；Variety                                              15<；br>；Veracity                                             16<；br>；Value                                               16<；br>；Different Types of Data                               17<；br>；Structured Data                                        18<；br>；Unstructured Data                                      19<；br>；Semi-structured Data                                  19<；br>；Metadata                                             20<；br>；Case Study Background                               20<；br>；History                                              20<；br>；Technical Infrastructure and Automation Environment         21<；br>；Business Goals and Obstacles                           22<；br>；Case Study Example                                24<；br>；Identifying Data Characteristics                          26<；br>；Volume                                                  26<；br>；Velocity                                                  26<；br>；Variety                                                   26<；br>；Veracity                                                  26<；br>；Value                                                  27<；br>；Identifying Types of Data                                 27<；br>；CHAPTER 2: Business Motivations and Drivers for Big Data Adoption                 29<；br>；Marketplace Dynamics                                30<；br>；Business Architecture                                 33<；br>；Business Process Management                         36<；br>；Information and Communications Technology             37<；br>；Data Analytics and Data Science                          37<；br>；Digitization                                            38<；br>；Affordable Technology and Commodity Hardware             38<；br>；Social Media                                         39<；br>；Hyper-Connected Communities and Devices               40<；br>；Cloud Computing                                     40<；br>；Internet of Everything (IoE)                             42<；br>；Case Study Example                                43<；br>；CHAPTER 3: Big Data Adoption and Planning Considerations                    47<；br>Organization Prerequisites                            49<br>Data Procurement                                    49<br>Privacy                                           49<br>Security                                            50<br>Provenance                                         51<br>Limited Realtime Support                             52<br>Distinct Performance Challenges                       53<br>Distinct Governance Requirements                     53<br>Distinct Methodology                                53<br>Clouds                                             54<br>Big Data Analytics Lifecycle                            55<br>Business Case Evaluation                                56<br>Data Identification                                      57<br>Data Acquisition and Filtering                             58<br>Data Extraction                                       60<br>Data Validation and Cleansing                           62<br>Data Aggregation and Representation                     64<br>Data Analysis                                         66<br>Data Visualization                                     68<br>Utilization of Analysis Results                            69<br>Cas