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• Half-title
• Reviews
• Title page
• Copyright information
• Brief Contents
• Table of contents
• About the Authors
• Preface
• Who This Book is For
• Topics Covered in this Book
• How to Read this Book
• Cross-Chapter Case Study: Sober
• Additional Material
• Acknowledgments
• Sober: 1000‰ Driven by Technology
• Part I Databases and Database Design
• 1 Fundamental Concepts of Database Management
• 1.1 Applications of Database Technology
• 1.2 Key Definitions
• 1.3 File versus Database Approach to Data Management
• 1.3.1 The File-Based Approach
• 1.3.2 The Database Approach
• 1.4 Elements of a Database System
• 1.4.1 Database Model versus Instances
• 1.4.2 Data Model
• 1.4.3 The Three-Layer Architecture
• 1.4.4 Catalog
• 1.4.5 Database Users
• 1.4.6 Database Languages
• 1.5 Advantages of Database Systems and Database Management
• 1.5.1 Data Independence
• 1.5.2 Database Modeling
• 1.5.3 Managing Structured, Semi-Structured, and Unstructured Data
• 1.5.4 Managing Data Redundancy
• 1.5.5 Specifying Integrity Rules
• 1.5.6 Concurrency Control
• 1.5.7 Backup and Recovery Facilities
• 1.5.8 Data Security
• 1.5.9 Performance Utilities
• Summary
• Problems and Exercises
• 2 Architecture and Categorization of DBMSs
• 2.1 Architecture of a DBMS
• 2.1.1 Connection and Security Manager
• 2.1.2 DDL Compiler
• 2.1.3 Query Processor
• 2.1.3.1 DML Compiler
• 2.1.3.2 Query Parser and Query Rewriter
• 2.1.3.3 Query Optimizer
• 2.1.3.4 Query Executor
• 2.1.4 Storage Manager
• 2.1.4.1 Transaction Manager
• 2.1.4.2 Buffer Manager
• 2.1.4.3 Lock Manager
• 2.1.4.4 Recovery Manager
• 2.1.5 DBMS Utilities
• 2.1.6 DBMS Interfaces
• 2.2 Categorization of DBMSs
• 2.2.1 Categorization Based on Data Model
• 2.2.1.1 Hierarchical DBMSs
• 2.2.1.2 Network DBMSs
• 2.2.1.3 Relational DBMSs
• 2.2.1.4 Object-Oriented DBMSs
• 2.2.1.5 Object-Relational/Extended Relational DBMSs
• 2.2.1.6 XML DBMSs
• 2.2.1.7 NoSQL DBMSs
• 2.2.2 Categorization Based on Degree of Simultaneous Access
• 2.2.3 Categorization Based on Architecture
• 2.2.4 Categorization Based on Usage
• Summary
• Problems and Exercises
• 3 Conceptual Data Modeling Using the (E)ER Model and UML Class Diagram
• 3.1 Phases of Database Design
• 3.2 The Entity Relationship Model
• 3.2.1 Entity Types
• 3.2.2 Attribute Types
• 3.2.3.1 Domains
• 3.2.3.2 Key Attribute Types
• 3.2.3.3 Simple versus Composite Attribute Types
• 3.2.3.4 Single-Valued versus Multi-Valued Attribute Types
• 3.2.3.5 Derived Attribute Type
• 3.2.4 Relationship Types
• 3.2.4.1 Degree and Roles
• 3.2.4.2 Cardinalities
• 3.2.4.3 Relationship Attribute Types
• 3.2.5 Weak Entity Types
• 3.2.6 Ternary Relationship Types
• 3.2.7 Examples of the ER Model
• 3.2.8 Limitations of the ER Model
• 3.3 The Enhanced Entity Relationship (EER) Model
• 3.3.1 Specialization/Generalization
• 3.3.2 Categorization
• 3.3.3 Aggregation
• 3.3.4 Examples of the EER Model
• 3.3.5 Designing an EER Model
• 3.4 The UML Class Diagram
• 3.4.1 Recap of Object Orientation
• 3.4.2 Classes
• 3.4.3 Variables
• 3.4.4 Access Modifiers
• 3.4.5 Associations
• 3.4.5.1 Association Class
• 3.4.5.2 Unidirectional versus Bidirectional Association
• 3.4.5.3 Qualified Association
• 3.4.6 Specialization/Generalization
• 3.4.7 Aggregation
• 3.4.8 UML Example
• 3.4.9 Advanced UML Modeling Concepts
• 3.4.9.1 Changeability Property
• 3.4.9.2 Object Constraint Language (OCL)
• 3.4.9.3 Dependency Relationship
• 3.4.10 UML versus EER
• Summary
• Problems and Exercises
• 4 Organizational Aspects of Data Management
• 4.1 Data Management
• 4.1.1 Catalogs and the Role of Metadata
• 4.1.2 Metadata Modeling
• 4.1.3 Data Quality
• 4.1.3.1 Data Quality Dimensions
• Accuracy
• Completeness
• Consistency
• Accessibility
• 4.1.3.2 Data Quality Problems
• 4.1.4 Data Governance
• 4.2 Roles in Data Management
• 4.2.1 Information Architect
• 4.2.2 Database Designer
• 4.2.3 Data Owner
• 4.2.4 Data Steward
• 4.2.5 Database Administrator
• 4.2.6 Data Scientist
• Summary
• Problems and Exercises
• Part II Types of Database Systems
• 5 Legacy Databases
• 5.1 The Hierarchical Model
• 5.2 The CODASYL Model
• Summary
• Problems and Exercises
• 6 Relational Databases: The Relational Model
• 6.1 The Relational Model
• 6.1.1 Basic Concepts
• 6.1.2 Formal Definitions
• 6.1.3 Types of Keys
• 6.1.3.1 Superkeys and Keys
• 6.1.3.2 Candidate Keys, Primary Keys, and Alternative Keys
• 6.1.3.3 Foreign Keys
• 6.1.4 Relational Constraints
• 6.1.5 Example Relational Data Model
• 6.2 Normalization
• 6.2.1 Insertion, Deletion, and Update Anomalies in an Unnormalized Relational Model
• 6.2.2 Informal Normalization Guidelines
• 6.2.3 Functional Dependencies and Prime Attribute Types
• 6.2.4 Normalization Forms
• 6.2.4.1 First Normal Form (1NF)
• 6.2.4.2 Second Normal Form (2NF)
• 6.2.4.3 Third Normal Form (3NF)
• 6.2.4.4 Boyce–Codd Normal Form (BCNF)
• 6.2.4.5 Fourth Normal Form (4NF)
• 6.3 Mapping a Conceptual ER Model to a Relational Model
• 6.3.1 Mapping Entity Types
• 6.3.2 Mapping Relationship Types
• 6.3.2.1 Mapping a Binary 1:1 Relationship type
• 6.3.2.2 Mapping a Binary 1:N Relationship Type
• 6.3.2.3 Mapping a Binary M:N Relationship Type
• 6.3.2.4 Mapping Unary Relationship Types
• 6.3.2.5 Mapping n-ary Relationship Types
• 6.3.3 Mapping Multi-Valued Attribute Types
• 6.3.4 Mapping Weak Entity Types
• 6.3.5 Putting it All Together
• 6.4 Mapping a Conceptual EER Model to a Relational Model
• 6.4.1 Mapping an EER Specialization
• 6.4.2 Mapping an EER Categorization
• 6.4.3 Mapping an EER Aggregation
• Summary
• Problems and Exercises
• 7 Relational Databases: Structured Query Language (SQL)
• 7.1 Relational Database Management Systems and SQL
• 7.1.1 Key Characteristics of SQL
• 7.1.2 Three-Layer Database Architecture
• 7.2 SQL Data Definition Language
• 7.2.1 Key DDL Concepts
• 7.2.2 DDL Example
• 7.2.3 Referential Integrity Constraints
• 7.2.4 DROP and ALTER Command
• 7.3 SQL Data Manipulation Language
• 7.3.1 SQL SELECT Statement
• 7.3.1.1 Simple Queries
• 7.3.1.2 Queries with Aggregate Functions
• 7.3.1.3 Queries with GROUP BY/HAVING
• 7.3.1.4 Queries with ORDER BY
• 7.3.1.5 Join Queries
• Inner Joins
• Outer Joins
• 7.3.1.6 Nested Queries
• 7.3.1.7 Correlated Queries
• 7.3.1.8 Queries with ALL/ANY
• 7.3.1.9 Queries with EXISTS
• 7.3.1.10 Queries with Subqueries in SELECT/FROM
• 7.3.1.11 Queries with Set Operations
• 7.3.2 SQL INSERT Statement
• 7.3.3 SQL DELETE Statement
• 7.3.4 SQL UPDATE Statement
• 7.4 SQL Views
• 7.5 SQL Indexes
• 7.6 SQL Privileges
• 7.7 SQL for Metadata Management
• Summary
• Problems and Exercises
• 8 Object-Oriented Databases and Object Persistence
• 8.1 Recap: Basic Concepts of OO
• 8.2 Advanced Concepts of OO
• 8.2.1 Method Overloading
• 8.2.2 Inheritance
• 8.2.3 Method Overriding
• 8.2.4 Polymorphism and Dynamic Binding
• 8.3 Basic Principles of Object Persistence
• 8.3.1 Serialization
• 8.4 OODBMS
• 8.4.1 Object Identifiers
• 8.4.2 ODMG Standard
• 8.4.3 Object Model
• 8.4.4 Object Definition Language (ODL)
• 8.4.5 Object Query Language (OQL)
• 8.4.5.1 Simple OQL Queries
• 8.4.5.2 SELECT FROM WHERE OQL Queries
• 8.4.5.3 Join OQL Queries
• 8.4.5.4 Other OQL Queries
• 8.4.6 Language Bindings
• 8.5 Evaluating OODBMSs
• Summary
• Problems and Exercises
• 9 Extended Relational Databases
• 9.1 Limitations of the Relational Model
• 9.2 Active RDBMS Extensions
• 9.2.1 Triggers
• 9.2.2 Stored Procedures
• 9.3 Object-Relational RDBMS Extensions
• 9.3.1 User-Defined Types
• 9.3.1.1 Distinct Data Types
• 9.3.1.2 Opaque Data Types
• 9.3.1.3 Unnamed Row Types
• 9.3.1.4 Named Row Types
• 9.3.1.5 Table Data Types
• 9.3.2 User-Defined Functions
• 9.3.3 Inheritance
• 9.3.3.1 Inheritance at Data Type Level
• 9.3.3.2 Inheritance at Table Type Level
• 9.3.4 Behavior
• 9.3.5 Polymorphism
• 9.3.6 Collection Types
• 9.3.7 Large Objects
• 9.4 Recursive SQL Queries
• Summary
• Problems and Exercises
• 10 XML Databases
• 10.1 Extensible Markup Language
• 10.1.1 Basic Concepts
• 10.1.2 Document Type Definition and XML Schema Definition
• 10.1.3 Extensible Stylesheet Language
• 10.1.4 Namespaces
• 10.1.5 XPath
• 10.2 Processing XML Documents
• 10.3 Storage of XML Documents
• 10.3.1 The Document-Oriented Approach for Storing XML Documents
• 10.3.2 The Data-Oriented Approach for Storing XML Documents
• 10.3.3 The Combined Approach for Storing XML Documents
• 10.4 Differences Between XML Data and Relational Data
• 10.5 Mappings Between XML Documents and (Object-) Relational Data
• 10.5.1 Table-Based Mapping
• 10.5.2 Schema-Oblivious Mapping
• 10.5.3 Schema-Aware Mapping
• 10.5.4 SQL/XML
• 10.6 Searching XML Data
• 10.6.1 Full-Text Search
• 10.6.2 Keyword-Based Search
• 10.6.3 Structured Search With XQuery
• 10.6.4 Semantic Search With RDF and SPARQL
• 10.7 XML for Information Exchange
• 10.7.1 Message-Oriented Middleware
• 10.7.2 SOAP-Based Web Services
• 10.7.3 REST-Based Web Services
• 10.7.4 Web Services and Databases
• 10.8 Other Data Representation Formats
• Summary
• Problems and Exercises
• 11 NoSQL Databases
• 11.1 The NoSQL Movement
• 11.1.1 The End of the ‘‘One Size Fits All’’ Era?
• 11.1.2 The Emergence of the NoSQL Movement
• 11.2 Key–Value Stores
• 11.2.1 From Keys to Hashes
• 11.2.2 Horizontal Scaling
• 11.2.3 An Example: Memcached
• 11.2.4 Request Coordination
• 11.2.5 Consistent Hashing
• 11.2.6 Replication and Redundancy
• 11.2.7 Eventual Consistency
• 11.2.8 Stabilization
• 11.2.9 Integrity Constraints and Querying
• 11.3 Tuple and Document Stores
• 11.3.1 Items with Keys
• 11.3.2 Filters and Queries
• 11.3.3 Complex Queries and Aggregation with MapReduce
• 11.3.4 SQL After All. . .
• 11.4 Column-Oriented Databases
• 11.5 Graph-Based Databases
• 11.5.1 Cypher Overview
• 11.5.2 Exploring a Social Graph
• 11.6 Other NoSQL Categories
• Summary
• Problems and Exercises
• Part III Physical Data Storage, Transaction Management, and Database Access
• 12 Physical File Organization and Indexing
• 12.1 Storage Hardware and Physical Database Design
• 12.1.1 The Storage Hierarchy
• 12.1.2 Internals of Hard Disk Drives
• 12.1.3 From Logical Concepts to Physical Constructs
• 12.2 Record Organization
• 12.3 File Organization
• 12.3.1 Introductory Concepts: Search Keys, Primary, and Secondary File Organization
• 12.3.2 Heap File Organization
• 12.3.3 Sequential File Organization
• 12.3.4 Random File Organization (Hashing)
• 12.3.4.1 Key-to-Address Transformation
• 12.3.4.2 Factors that Determine the Efficiency of Random File Organization
• 12.3.5 Indexed Sequential File Organization
• 12.3.5.1 Basic Terminology of Indexes
• 12.3.5.2 Primary Indexes
• 12.3.5.3 Clustered Indexes
• 12.3.5.4 Multilevel Indexes
• 12.3.6 List Data Organization (Linear and Nonlinear Lists)
• 12.3.6.1 Linear Lists
• 12.3.6.2 Tree Data Structures
• 12.3.7 Secondary Indexes and Inverted Files
• 12.3.7.1 Characteristics of Secondary Indexes
• 12.3.7.2 Inverted Files
• 12.3.7.3 Multicolumn Indexes
• 12.3.7.4 Other Index Types
• 12.3.8 B-Trees and B+-Trees
• 12.3.8.1 Multilevel Indexes Revisited
• 12.3.8.2 Binary Search Trees
• 12.3.8.3 B-Trees
• 12.3.8.4 B+-Trees
• Summary
• Problems and Exercises
• 13 Physical Database Organization
• 13.1 Physical Database Organization and Database Access Methods
• 13.1.1 From Database to Tablespace
• 13.1.2 Index Design
• 13.1.3 Database Access Methods
• 13.1.3.1 Functioning of the Query Optimizer
• 13.1.3.2 Index Search (with Atomic Search Key)
• 13.1.3.3 Multiple Index and Multicolumn Index Search
• 13.1.3.4 Index-Only Access
• 13.1.3.5 Full Table Scan
• 13.1.4 Join Implementations
• 13.1.4.1 Nested-Loop Join
• 13.1.4.2 Sort-Merge Join
• 13.1.4.3 Hash Join
• 13.2 Enterprise Storage Subsystems and Business Continuity
• 13.2.1 Disk Arrays and RAID
• 13.2.2 Enterprise Storage Subsystems
• 13.2.2.1 Overview and Classification
• 13.2.2.2 DAS (Directly Attached Storage)
• 13.2.2.3 SAN (Storage Area Network)
• 13.2.2.4 NAS (Network Attached Storage)
• 13.2.2.5 NAS Gateway
• 13.2.2.6 iSCSI/Storage Over IP
• 13.2.3 Business Continuity
• 13.2.3.1 Contingency Planning, Recovery Point, and Recovery Time
• 13.2.3.2 Availability and Accessibility of Storage Devices
• 13.2.3.3 Availability of Database Functionality
• 13.2.3.4 Data Availability
• Summary
• Problems and Exercises
• 14 Basics of Transaction Management
• 14.1 Transactions, Recovery, and Concurrency Control
• 14.2 Transactions and Transaction Management
• 14.2.1 Delineating Transactions and the Transaction Lifecycle
• 14.2.2 DBMS Components Involved in Transaction Management
• 14.2.3 The Logfile
• 14.3 Recovery
• 14.3.1 Types of Failures
• 14.3.2 System Recovery
• 14.3.3 Media Recovery
• 14.4 Concurrency Control
• 14.4.1 Typical Concurrency Problems
• 14.4.1.1 Lost Update Problem
• 14.4.1.2 Uncommitted Dependency Problem (aka Dirty Read Problem)
• 14.4.1.3 Inconsistent Analysis Problem
• 14.4.1.4 Other Concurrency-Related Problems
• 14.4.2 Schedules and Serial Schedules
• 14.4.3 Serializable Schedules
• 14.4.4 Optimistic and Pessimistic Schedulers
• 14.4.5 Locking and Locking Protocols
• 14.4.5.1 Purposes of Locking
• 14.4.5.2 The Two-Phase Locking Protocol (2PL)
• 14.4.5.3 Cascading Rollbacks
• 14.4.5.4 Dealing with Deadlocks
• 14.4.5.5 Isolation Levels
• 14.4.5.6 Lock Granularity
• 14.5 The ACID Properties of Transactions
• Summary
• Problems and Exercises
• 15 Accessing Databases and Database APIs
• 15.1 Database System Architectures
• 15.1.1 Centralized System Architectures
• 15.1.2 Tiered System Architectures
• 15.2 Classification of Database APIs
• 15.2.1 Proprietary versus Universal APIs
• 15.2.2 Embedded versus Call-Level APIs
• 15.2.3 Early Binding versus Late Binding
• 15.3 Universal Database APIs
• 15.3.1 ODBC
• 15.3.2 OLE DB and ADO
• 15.3.3 ADO.NET
• 15.3.4 Java DataBase Connectivity (JDBC)
• 15.3.5 Intermezzo: SQL Injection and Access Security
• 15.3.6 SQLJ
• 15.3.7 Intermezzo: Embedded APIs versus Embedded DBMSs
• 15.3.8 Language-Integrated Querying
• 15.4 Object Persistence and Object-Relational Mapping APIs
• 15.4.1 Object Persistence with Enterprise JavaBeans
• 15.4.2 Object Persistence with the Java Persistence API
• 15.4.3 Object Persistence with Java Data Objects
• 15.4.4 Object Persistence in Other Host Languages
• 15.5 Database API Summary
• 15.6 Database Access in the World Wide Web
• 15.6.1 Introduction: the Original Web Server
• 15.6.2 The Common Gateway Interface: Toward Dynamic Web Pages
• 15.6.3 Client-Side Scripting: The Desire for a Richer Web
• 15.6.4 JavaScript as a Platform
• 15.6.5 DBMSs Adapt: REST, Other Web Services, and a Look Ahead
• Summary
• Problems and Exercises
• 16 Data Distribution and Distributed Transaction Management
• 16.1 Distributed Systems and Distributed Databases
• 16.2 Architectural Implications of Distributed Databases
• 16.3 Fragmentation, Allocation, and Replication
• 16.3.1 Vertical Fragmentation
• 16.3.2 Horizontal Fragmentation (Sharding)
• 16.3.3 Mixed Fragmentation
• 16.3.4 Replication
• 16.3.5 Distribution and Replication of Metadata
• 16.4 Transparency
• 16.5 Distributed Query Processing
• 16.6 Distributed Transaction Management and Concurrency Control
• 16.6.1 Primary Site and Primary Copy 2PL
• 16.6.2 Distributed 2PL
• 16.6.3 The Two-Phase Commit Protocol (2PC)
• 16.6.4 Optimistic Concurrency and Loosely Coupled Systems
• 16.6.5 Compensation-Based Transaction Models
• 16.7 Eventual Consistency and BASE Transactions
• 16.7.1 Horizontal Fragmentation and Consistent Hashing
• 16.7.2 The CAP Theorem
• 16.7.3 BASE Transactions
• 16.7.4 Multi-Version Concurrency Control and Vector Clocks
• 16.7.5 Quorum-Based Consistency
• Summary
• Problems and Exercises
• Part IV Data Warehousing, Data Governance, and (Big) Data Analytics
• 17 Data Warehousing and Business Intelligence
• 17.1 Operational versus Tactical/Strategic Decision-Making
• 17.2 Data Warehouse Definition
• 17.3 Data Warehouse Schemas
• 17.3.1 Star Schema
• 17.3.2 Snowflake Schema
• 17.3.3 Fact Constellation
• 17.3.4 Specific Schema Issues
• 17.3.4.1 Surrogate Keys
• 17.3.4.2 Granularity of the Fact Table
• 17.3.4.3 Factless Fact Tables
• 17.3.4.4 Optimizing the Dimension Tables
• 17.3.4.5 Defining Junk Dimensions
• 17.3.4.6 Defining Outrigger Tables
• 17.3.4.7 Slowly Changing Dimensions
• 17.3.4.8 Rapidly Changing Dimensions
• 17.4 The Extraction, Transformation, and Loading (ETL) Process
• 17.5 Data Marts
• 17.6 Virtual Data Warehouses and Virtual Data Marts
• 17.7 Operational Data Store
• 17.8 Data Warehouses versus Data Lakes
• 17.9 Business Intelligence
• 17.9.1 Query and Reporting
• 17.9.2 Pivot Tables
• 17.9.3 On-Line Analytical Processing (OLAP)
• 17.9.3.1 MOLAP
• 17.9.3.2 ROLAP
• 17.9.3.3 HOLAP
• 17.9.3.4 OLAP Operators
• 17.9.3.5 OLAP Queries in SQL
• Summary
• Problems and Exercises
• 18 Data Integration, Data Quality, and Data Governance
• 18.1 Data and Process Integration
• 18.1.1 Convergence of Analytical and Operational Data Needs
• 18.1.2 Data Integration and Data Integration Patterns
• 18.1.2.1 Data Consolidation: Extract, Transform, Load (ETL)
• 18.1.2.2 Data Federation: Enterprise Information Integration (EII)
• 18.1.2.3 Data Propagation: Enterprise Application Integration (EAI)
• 18.1.2.4 Data Propagation: Enterprise Data Replication (EDR)
• 18.1.2.5 Changed Data Capture (CDC), Near-Real-Time ETL, and Event Processing
• 18.1.2.6 Data Virtualization
• 18.1.2.7 Data as a Service and Data in the Cloud
• 18.1.3 Data Services and Data Flows in the Context of Data and Process Integration
• 18.1.3.1 Business Process Integration
• 18.1.3.2 Patterns for Managing Sequence Dependencies and Data Dependencies in Processes
• 18.1.3.3 A Unified View on Data and Process Integration
• 18.2 Searching Unstructured Data and Enterprise Search
• 18.2.1 Principles of Full-Text Search
• 18.2.2 Indexing Full-Text Documents
• 18.2.3 Web Search Engines
• 18.2.4 Enterprise Search
• 18.3 Data Quality and Master Data Management
• 18.4 Data Governance
• 18.4.1 Total Data Quality Management (TDQM)
• 18.4.2 Capability Maturity Model Integration (CMMI)
• 18.4.3 Data Management Body of Knowledge (DMBOK)
• 18.4.4 Control Objectives for Information and Related Technology (COBIT)
• 18.4.5 Information Technology Infrastructure Library
• 18.5 Outlook
• 18.6 Conclusion
• Problems and Exercises
• 19 Big Data
• 19.1 The 5 Vs of Big Data
• 19.2 Hadoop
• 19.2.1 History of Hadoop
• 19.2.2 The Hadoop Stack
• 19.2.2.1 The Hadoop Distributed File System
• 19.2.2.2 MapReduce
• 19.2.2.3 Yet Another Resource Negotiator
• 19.3 SQL on Hadoop
• 19.3.1 HBase: The First Database on Hadoop
• 19.3.2 Pig
• 19.3.3 Hive
• 19.4 Apache Spark
• 19.4.1 Spark Core
• 19.4.2 Spark SQL
• 19.4.3 MLlib, Spark Streaming, and GraphX
• 19.5 Conclusion
• Problems and Exercises
• 20 Analytics
• 20.1 The Analytics Process Model
• 20.2 Example Analytics Applications
• 20.3 Data Scientist Job Profile
• 20.4 Data Pre-Processing
• 20.4.1 Denormalizing Data for Analysis
• 20.4.2 Sampling
• 20.4.3 Exploratory Analysis
• 20.4.4 Missing Values
• 20.4.5 Outlier Detection and Handling
• 20.5 Types of Analytics
• 20.5.1 Predictive Analytics
• 20.5.1.1 Linear Regression
• 20.5.1.2 Logistic Regression
• Logistic Regression Properties
• 20.5.1.3 Decision Trees
• Splitting Decision
• Stopping Decision
• Decision Tree Properties
• Regression Trees
• 20.5.1.4 Other Predictive Analytics Techniques
• 20.5.2 Evaluating Predictive Models
• 20.5.2.1 Splitting Up the Dataset
• 20.5.2.2 Performance Measures for Classification Models
• 20.5.2.3 Performance Measures for Regression Models
• 20.5.2.4 Other Performance Measures for Predictive Analytical Models
• 20.5.3 Descriptive Analytics
• 20.5.3.1 Association Rules
• Basic Setting
• Support, Confidence, and Lift
• Post-Processing Association Rules
• 20.5.3.2 Sequence Rules
• 20.5.3.3 Clustering
• Hierarchical Clustering
• K-means Clustering
• 20.5.4 Social Network Analytics
• 20.5.4.1 Social Network Definitions
• 20.5.4.2 Social Network Metrics
• 20.5.4.3 Social Network Learning
• 20.6 Post-Processing of Analytical Models
• 20.7 Critical Success Factors for Analytical Models
• 20.8 Economic Perspective on Analytics
• 20.8.1 Total Cost of Ownership (TCO)
• 20.8.2 Return on Investment
• 20.8.3 In- versus Outsourcing
• 20.8.4 On-Premises versus Cloud Solutions
• 20.8.5 Open-Source versus Commercial Software
• 20.9 Improving the ROI of Analytics
• 20.9.1 New Sources of Data
• 20.9.2 Data Quality
• 20.9.3 Management Support
• 20.9.4 Organizational Aspects
• 20.9.5 Cross-Fertilization
• 20.10 Privacy and Security
• 20.10.1 Overall Considerations Regarding Privacy and Security
• 20.10.2 The RACI Matrix
• 20.10.3 Accessing Internal Data
• 20.10.3.1 Anonymization
• 20.10.3.2 SQL Views
• 20.10.3.3 Label-Based Access Control
• 20.10.4 Privacy Regulation
• 20.11 Conclusion
• Problems and Exercises
• Appendix Using the Online Environment
• How to Access the Online Environment
• Environment: Relational Databases and SQL
• Environment: MongoDB
• Environment: Neo4j and Cypher
• Environment: Tree Structure Visualizations
• Environment: HBase
• Glossary
• Index
• Endorsements