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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

UM RAFBÆKUR Á HEIMKAUP.IS

Bókahillan þín er þitt svæði og þar eru bækurnar þínar geymdar. Þú kemst í bókahilluna þína hvar og hvenær sem er í tölvu eða snjalltæki. Einfalt og þægilegt!

Rafbók til eignar
Rafbók til eignar þarf að hlaða niður á þau tæki sem þú vilt nota innan eins árs frá því bókin er keypt.

Þú kemst í bækurnar hvar sem er
Þú getur nálgast allar raf(skóla)bækurnar þínar á einu augabragði, hvar og hvenær sem er í bókahillunni þinni. Engin taska, enginn kyndill og ekkert vesen (hvað þá yfirvigt).

Auðvelt að fletta og leita
Þú getur flakkað milli síðna og kafla eins og þér hentar best og farið beint í ákveðna kafla úr efnisyfirlitinu. Í leitinni finnur þú orð, kafla eða síður í einum smelli.

Glósur og yfirstrikanir
Þú getur auðkennt textabrot með mismunandi litum og skrifað glósur að vild í rafbókina. Þú getur jafnvel séð glósur og yfirstrikanir hjá bekkjarsystkinum og kennara ef þeir leyfa það. Allt á einum stað.

Hvað viltu sjá? / Þú ræður hvernig síðan lítur út
Þú lagar síðuna að þínum þörfum. Stækkaðu eða minnkaðu myndir og texta með multi-level zoom til að sjá síðuna eins og þér hentar best í þínu námi.



Fleiri góðir kostir
- Þú getur prentað síður úr bókinni (innan þeirra marka sem útgefandinn setur)
- Möguleiki á tengingu við annað stafrænt og gagnvirkt efni, svo sem myndbönd eða spurningar úr efninu
- Auðvelt að afrita og líma efni/texta fyrir t.d. heimaverkefni eða ritgerðir
- Styður tækni sem hjálpar nemendum með sjón- eða heyrnarskerðingu