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Database Management Systems

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Topics 10

Introduction to Database Management Systems
Overview of database management systems (DBMS), their importance in modern information sys...
Relational Database Model
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SQL Fundamentals
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Database Design and Modeling
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Database Security and Integrity
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Indexing and Query Optimization
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Transaction Management and Concurrency Control
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Database Connectivity and Application Development
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NoSQL Databases
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Big Data and Distributed Databases
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Unit Outline 40h

Learning Objectives

5 objectives
  • Understand the fundamental concepts and components of database management systems (DBMS).
  • Apply relational database modeling techniques, including normalization and entity-relationship diagrams.
  • Develop proficiency in SQL for data definition, manipulation, and retrieval.
  • Explore advanced topics such as database security, indexing, transaction management, and concurrency control.
  • Gain an overview of NoSQL databases and big data technologies for handling large-scale, unstructured data.

Content Outline

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Unit 614: Database Management Systems and Big Data Technologies

1. Introduction to Database Management Systems

  • Definition and purpose of DBMS
  • Importance of DBMS in modern information systems
  • Basic concepts: data, database, DBMS software
  • Components of DBMS: DBMS engine, database schema, query processor, transaction manager
  • Types of DBMS (brief overview)

2. Relational Database Model

  • Fundamentals of the relational model
  • Terminology: tables (relations), rows (tuples), columns (attributes)
  • Keys: primary keys, foreign keys, candidate keys
  • Relationships: one-to-one, one-to-many, many-to-many
  • Normalization techniques:
    • Purpose of normalization
    • Normal forms (1NF, 2NF, 3NF, BCNF)
    • Denormalization considerations

3. SQL Fundamentals

  • Introduction to Structured Query Language (SQL)
  • Data Definition Language (DDL): CREATE, ALTER, DROP
  • Data Manipulation Language (DML): SELECT, INSERT, UPDATE, DELETE
  • Data Control Language (DCL): GRANT, REVOKE (briefly)
  • Query basics: filtering, sorting, joining tables
  • Aggregate functions and grouping data

4. Database Design and Modeling

  • Importance of database design
  • Entity-Relationship Diagrams (ERD): entities, attributes, relationships
  • Mapping ERD to relational schema
  • Use of data modeling tools (e.g., ERwin, MySQL Workbench)
  • Best practices for efficient and scalable database structures

5. Database Security and Integrity

  • Database security principles
  • Access control models: discretionary, mandatory, role-based
  • Authentication and authorization mechanisms
  • Encryption techniques for data protection
  • Data integrity enforcement:
    • Constraints (primary key, foreign key, unique, check)
    • Triggers
    • Transaction management fundamentals

6. Indexing and Query Optimization

  • Purpose and types of indexing:
    • B-tree, Hash indexes
  • Query execution plans
  • Query optimization techniques
  • Performance tuning strategies
  • Understanding and analyzing database profiler tools

7. Transaction Management and Concurrency Control

  • Definition of a database transaction
  • ACID properties: Atomicity, Consistency, Isolation, Durability
  • Isolation levels and their impact
  • Concurrency control mechanisms:
    • Locking strategies (pessimistic and optimistic)
    • Deadlock detection and resolution
  • Handling data consistency in multi-user environments

8. Database Connectivity and Application Development

  • Database connectivity concepts
  • Connecting to databases using programming languages (Java JDBC, Python DB-API)
  • Implementing CRUD operations programmatically
  • Managing database transactions within applications
  • Error handling and resource management

9. NoSQL Databases

  • Introduction to NoSQL and its emergence
  • Types of NoSQL databases:
    • Document-oriented (e.g., MongoDB)
    • Key-value stores (e.g., Redis)
    • Column-family stores (e.g., Cassandra)
    • Graph databases (e.g., Neo4j)
  • Differences between NoSQL and relational databases
  • Use cases and scenarios for NoSQL

10. Big Data and Distributed Databases

  • Overview of big data concepts
  • Distributed database systems and architectures
  • Challenges in scalability and data consistency
  • Data partitioning and replication strategies
  • Parallel processing frameworks
  • Technologies overview:
    • Hadoop ecosystem
    • Apache Spark
  • Applications in managing and analyzing massive datasets
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