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Data Modeling Tutorial by Ajay Kumar
Jun 28, 2024
Data Modeling Tutorial by Ajay Kumar
Introduction
Presented by Ajay Kumar
11+ years experience in data field
Tutorial covers basics to advanced concepts
Workshop at the end focused on Power BI
Sections Overview
Data Modeling Overview
What is data modeling?
Why use data modeling?
Techniques in data modeling
Types of data models
Advantages and disadvantages of data models
Fact and Dimension Tables
Definitions and importance of fact and dimension tables
Primary key & Foreign key
Different types of facts (Additive, Semi-additive, Non-additive)
Relationships in Data Modeling
Types of relationships (One-to-One, One-to-Many, Many-to-Many)
Importance and practical implementation
Cardinality and connectivity
Schema in Data Modeling
Types of schemas (Star, Snowflake, Galaxy)
Advantages and disadvantages
Workshop in Power BI
Hands-on experience
Managing relationships
Connecting fact and dimension tables
Quizzes for knowledge check
Key Points Covered
Data Modeling Overview
Definition
: Creating a conceptual representation of data objects and their relationships/rules.
Importance
: Visual representation, enforcing business rules, regulatory compliance, ensuring data quality.
Data Modeling Techniques
:
Entity Relationship Model (ER)
Unified Modeling Language (UML)
Data Model Types
:
Conceptual: High-level, business-focused
Logical: Technical, rules, and data structures
Physical: Database-specific implementation
Fact and Dimension Tables
Fact Table
: Primary table, contains numeric data/measures.
Dimension Table
: Structure to categorize facts, descriptive attributes.
Primary Key
: Unique identifier, no null values.
Foreign Key
: Reference key in another table, can have non-unique values.
Types of Facts
:
Additive: Can apply all functions
Semi-additive: Some functions applicable
Non-additive: No aggregate functions apply
Relationships in Data Modeling
Types
:
One-to-One: Single unique record per table connection
One-to-Many: Single record in one table relates to many in another
Many-to-Many: Multiple records in both tables relate to each other
Cardinality
: Expresses the minimum and maximum number of entity occurrences
Preventing Duplication
: Using bridge tables or join tables
Best Practices
: Spend time on data modeling, ensure proper relationships
Schema in Data Modeling
Star Schema
: Single fact table related to dimension tables
Simplified, optimized for large data sets
Denormalized structure
Snowflake Schema
: Extension of star schema, normalized dimensions
Uses less disk space, more complex
Galaxy (Constellation) Schema
: Multiple fact tables sharing dimension tables
Useful for complex databases
Workshop in Power BI
Topics Covered
:
Loading data, creating relationships
Creating calculated columns, sorting, marking as date tables
Optimizing data model, hiding unused fields
Practical use of data models in Power BI
Creating and managing interactive reports
Important Concepts
:
Auto-detecting and managing relationships
Creating new columns and measures, using DAX functions
Practical applications and troubleshooting
Summary
Data modeling: vital for accurate data representation and querying
Types of data models and schemas: specific use cases and characteristics
Fact and dimension tables: importance and usage in data modeling
Relationships in data modeling: essential for querying and data integrity
Power BI workshop: practical experience in data modeling
Feedback and Questions
Ajay Kumar encourages feedback and questions
Reach out via LinkedIn or the provided description
Additional Resources
Quizzes to check knowledge
Money-back guarantee for unsatisfied participants
📄
Full transcript