Data Modeling Fundamentals

Data Modeling

• Data modeling is the process of creating a conceptual representation of data structures and relationships.
• Goals:
  • Simplify complex data systems
  • Improve communication among stakeholders
  • Guide database design
• Types of data models:
  • Conceptual data model (high-level, abstract)
  • Logical data model (semi-abstract, platform-independent)
  • Physical data model (detailed, platform-specific)
• Data modeling techniques:
  • Entity-Relationship (ER) modeling
  • Object-Relational Mapping (ORM)

Normalization

• Normalization is the process of organizing data in a database to minimize data redundancy and dependency.
• Goals:
  • Eliminate data redundancy
  • Reduce data anomalies
  • Improve data integrity
• Normalization rules:
  1. First Normal Form (1NF): Each table cell must contain a single value.
  2. Second Normal Form (2NF): Each non-key attribute in a table must depend on the entire primary key.
  3. Third Normal Form (3NF): If a table is in 2NF, and a non-key attribute depends on another non-key attribute, then it should be moved to a separate table.
  • Higher normal forms (Boyce-Codd Normal Form, 4NF, 5NF, etc.) exist, but are less commonly used.

Database Security

• Database security refers to the measures taken to protect a database from unauthorized access, use, disclosure, disruption, modification, or destruction.
• Threats:
  • Unauthorized access
  • SQL injection
  • Data breaches
  • Denial of Service (DoS) attacks
• Security measures:
  • Authentication and authorization
  • Access control lists (ACLs)
  • Encryption
  • Auditing and logging
  • Regular security updates and patches

Query Optimization

• Query optimization is the process of improving the efficiency of database queries to reduce response time and resource usage.
• Techniques:
  • Indexing: creating data structures to speed up query execution
  • Caching: storing frequently accessed data in memory
  • Query rewriting: rephrasing queries to use more efficient algorithms
  • Join optimization: optimizing the order and method of joining tables
  • Parallel processing: executing queries in parallel to reduce response time
• Query optimization tools:
  • Execution plan analysis
  • Query profiling
  • Index tuning wizards

Data Modeling

• Data modeling creates a conceptual representation of data structures and relationships to simplify complex data systems, improve communication, and guide database design.
• There are three types of data models: conceptual (high-level, abstract), logical (semi-abstract, platform-independent), and physical (detailed, platform-specific).
• Two data modeling techniques are Entity-Relationship (ER) modeling and Object-Relational Mapping (ORM).

Normalization

• Normalization organizes data in a database to minimize data redundancy and dependency, eliminating data redundancy, reducing data anomalies, and improving data integrity.
• Normalization rules include:
  • First Normal Form (1NF): each table cell must contain a single value.
  • Second Normal Form (2NF): each non-key attribute depends on the entire primary key.
  • Third Normal Form (3NF): non-key attributes that depend on other non-key attributes are moved to a separate table.
• Higher normal forms exist, such as Boyce-Codd Normal Form, 4NF, 5NF, etc.

Database Security

• Database security measures protect against unauthorized access, use, disclosure, disruption, modification, or destruction.
• Threats include unauthorized access, SQL injection, data breaches, and Denial of Service (DoS) attacks.
• Security measures include:
  • Authentication and authorization
  • Access control lists (ACLs)
  • Encryption
  • Auditing and logging
  • Regular security updates and patches

Query Optimization

• Query optimization improves the efficiency of database queries, reducing response time and resource usage.
• Techniques include:
  • Indexing: creating data structures to speed up query execution
  • Caching: storing frequently accessed data in memory
  • Query rewriting: rephrasing queries to use more efficient algorithms
  • Join optimization: optimizing the order and method of joining tables
  • Parallel processing: executing queries in parallel to reduce response time
• Query optimization tools include execution plan analysis, query profiling, and index tuning wizards.

Test your understanding of data modeling concepts, goals, and techniques. Learn about the different types of data models and their applications.