Principles of Database Management The Practical Guide to Stori Data 1st edition by Wilfried Lemahieu, Seppe vanden Broucke, Bart Baesens ISBN 1316952986 9781316952986

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ISBN 10: 1316952986
ISBN 13: 9781316952986
Author: Wilfried Lemahieu, Seppe vanden Broucke, Bart Baesens

This comprehensive textbook teaches the fundamentals of database design, modeling, systems, data storage, and the evolving world of data warehousing, governance and more. Written by experienced educators and experts in big data, analytics, data quality, and data integration, it provides an up-to-date approach to database management. This full-color, illustrated text has a balanced theory-practice focus, covering essential topics, from established database technologies to recent trends, like Big Data, NoSQL, and more. Fundamental concepts are supported by real-world examples, query and code walkthroughs, and figures, making it perfect for introductory courses for advanced undergraduates and graduate students in information systems or computer science. These examples are further supported by an online playground with multiple learning environments, including MySQL, MongoDB, Neo4j Cypher, and tree structure visualization. This combined learning approach connects key concepts throughout the text to the important, practical tools to get started in database management.

Principles of Database Management The Practical Guide to Stori Data 1st Table of contents:

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

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Tags: Wilfried Lemahieu, Seppe vanden Broucke, Bart Baesens, Stori Data, Database Management