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.