Big Data Fundamentals: Concepts, Drivers & Techniques

Content: Acknowledgments   xviiReader Services   xviiiPART I: THE FUNDAMENTALS OF BIG DATAChapter 1: Understanding Big Data   3Concepts and Terminology   5Datasets   5Data Analysis   6Data Analytics   6Descriptive Analytics   8Diagnostic Analytics   9Predictive Analytics   10Prescriptive Analytics   11Business Intelligence (BI)   12Key Performance Indicators (KPI)   12Big Data Characteristics   13Volume   14Velocity   14Variety   15Veracity   16Value   16Different Types of Data   17Structured Data   18Unstructured Data   19Semi-structured Data   19Metadata   20Case Study Background   20History   20Technical Infrastructure and Automation Environment   21Business Goals and Obstacles   22Case Study Example   24Identifying Data Characteristics   26Volume   26Velocity   26Variety   26Veracity   26Value   27Identifying Types of Data   27Chapter 2: Business Motivations and Drivers for Big Data Adoption   29Marketplace Dynamics   30Business Architecture   33Business Process Management   36Information and Communications Technology   37Data Analytics and Data Science   37Digitization   38Affordable Technology and Commodity Hardware   38Social Media   39Hyper-Connected Communities and Devices   40Cloud Computing   40Internet of Everything (IoE)   42Case Study Example   43Chapter 3: Big Data Adoption and Planning Considerations   47Organization Prerequisites   49Data Procurement   49Privacy   49Security   50Provenance   51Limited Realtime Support   52Distinct Performance Challenges   53Distinct Governance Requirements   53Distinct Methodology   53Clouds   54Big Data Analytics Lifecycle   55Business Case Evaluation   56Data Identification   57Data Acquisition and Filtering   58Data Extraction   60Data Validation and Cleansing   62Data Aggregation and Representation   64Data Analysis   66Data Visualization   68Utilization of Analysis Results   69Case Study Example   71Big Data Analytics Lifecycle   73Business Case Evaluation   73Data Identification   74Data Acquisition and Filtering   74Data Extraction   74Data Validation and Cleansing   75Data Aggregation and Representation   75Data Analysis   75Data Visualization   76Utilization of Analysis Results   76Chapter 4: Enterprise Technologies and Big Data Business Intelligence   77Online Transaction Processing (OLTP)   78Online Analytical Processing (OLAP)   79Extract Transform Load (ETL)   79Data Warehouses   80Data Marts   81Traditional BI   82Ad-hoc Reports   82Dashboards   82Big Data BI   84Traditional Data Visualization   84Data Visualization for Big Data   85Case Study Example   86Enterprise Technology   86Big Data Business Intelligence   87PART II: STORING AND ANALYZING BIG DATAChapter 5: Big Data Storage Concepts   91Clusters   93File Systems and Distributed File Systems   93NoSQL   94Sharding   95Replication   97Master-Slave   98Peer-to-Peer   100Sharding and Replication   103Combining Sharding and Master-Slave Replication   104Combining Sharding and Peer-to-Peer Replication   105CAP Theorem   106ACID   108BASE   113Case Study Example   117Chapter 6: Big Data Processing Concepts   119Parallel Data Processing   120Distributed Data Processing   121Hadoop   122Processing Workloads   122Batch   123Transactional   123Cluster   124Processing in Batch Mode   125Batch Processing with MapReduce   125Map and Reduce Tasks   126Map   127Combine   127Partition   129Shuffle and Sort   130Reduce   131A Simple MapReduce Example   133Understanding MapReduce Algorithms   134Processing in Realtime Mode   137Speed Consistency Volume (SCV)   137Event Stream Processing   140Complex Event Processing   141Realtime Big Data Processing and SCV   141Realtime Big Data Processing and MapReduce   142Case Study Example   143Processing Workloads   143Processing in Batch Mode   143Processing in Realtime   144Chapter 7: Big Data Storage Technology   145On-Disk Storage Devices   147Distributed File Systems   147RDBMS Databases   149NoSQL Databases   152Characteristics   152Rationale   153Types   154Key-Value   156Document   157Column-Family   159Graph   160NewSQL Databases   163In-Memory Storage Devices   163In-Memory Data Grids   166Read-through   170Write-through   170Write-behind   172Refresh-ahead   172In-Memory Databases   175Case Study Example   179Chapter 8: Big Data Analysis Techniques   181Quantitative Analysis   183Qualitative Analysis   184Data Mining   184Statistical Analysis   184A/B Testing   185Correlation   186Regression   188Machine Learning   190Classification (Supervised Machine Learning)   190Clustering (Unsupervised Machine Learning)   191Outlier Detection   192Filtering   193Semantic Analysis   195Natural Language Processing   195Text Analytics   196Sentiment Analysis   197Visual Analysis   198Heat Maps   198Time Series Plots   200Network Graphs   201Spatial Data Mapping   202Case Study Example   204Correlation   204Regression   204Time Series Plot   205Clustering   205Classification   205Appendix A: Case Study Conclusion   207About the Authors   211Thomas Erl   211Wajid Khattak   211Paul Buhler   212Index   213