SQLServer Tutorial - 11. Database Design and Modeling

11.1 Introduction to Database Design and Modeling

Overview of database design principles

Importance of effective database modeling

Key concepts: Entities, attributes, relationships, and tables


11.2 Entity-Relationship (ER) Modeling

Introduction to ER modeling

Entities, attributes, and relationships in ER diagrams

Cardinality and participation constraints

Mapping ER diagrams to relational schemas


11.3 Normalization and Denormalization

Understanding normalization and denormalization

Normal forms: First normal form (1NF) to Boyce-Codd normal form (BCNF)

Benefits and trade-offs of normalization and denormalization


11.4 Relational Schema Design

Conceptual, logical, and physical database design

Translating ER diagrams into relational schemas

Primary keys, foreign keys, and referential integrity constraints


11.5 Data Modeling Best Practices

Best practices for designing effective data models

Identifying and resolving data modeling challenges

Iterative and incremental data modeling process


11.6 Schema Refinement and Optimization

Refining and optimizing database schemas

Indexing strategies for improving query performance

Partitioning and clustering for efficient data storage and retrieval


11.7 Temporal and Spatial Data Modeling

Modeling temporal data: Effective dating, event tracking

Spatial data modeling: Geospatial data types, spatial indexing

Use cases and applications of temporal and spatial data modeling


11.8 Data Warehousing and Dimensional Modeling

Introduction to data warehousing concepts

Dimensional modeling techniques: Star schema, snowflake schema

Designing data marts and OLAP cubes


11.9 Modeling Complex Data Structures

Handling complex data structures in database modeling

Arrays, nested tables, and other composite data types

Techniques for modeling hierarchical data


11.10 Modeling for NoSQL Databases

Data modeling considerations for NoSQL databases

Document-oriented, key-value, columnar, and graph data modeling

Schema flexibility and dynamic schema evolution in NoSQL databases


11.11 Modeling for Big Data and Analytics

Designing data models for big data and analytics

Handling unstructured and semi-structured data

Data modeling techniques for machine learning and predictive analytics


11.12 Data Governance and Documentation

Establishing data governance policies and procedures

Documenting database designs and data dictionaries

Ensuring data quality and consistency through data governance practices


11.13 Data modeling best practices