Data Modeling in Power BI

Study Notes

Data Modeling: The process of creating a conceptual representation of data structures to support business analytics.
Importance: Proper data modeling is crucial for accurate and efficient data analysis, as it enables:
- Data consistency and integrity
- Improved data querying and reporting
- Enhanced data visualization and business insights
Key Concepts:
- Tables: Representing individual data entities, such as customers or orders
- Columns: Representing individual fields or attributes within a table
- Relationships: Defining connections between tables to enable data joining and analysis
- Measures: Calculated fields that perform aggregations or calculations on data
- Hierarchies: Organizing data into structured categories for easier analysis

Dashboard Design: The process of creating a visual representation of data to support business decision-making.
Key Principles:
- Clear and Concise: Effective communication of insights through minimalism and simplicity
- Focused Storytelling: Guiding the user through a narrative of key findings and insights
- Interactive and Dynamic: Enabling users to explore and analyze data through interactive visualizations
- Consistent and Standardized: Maintaining a consistent design language throughout the dashboard
Best Practices:
- Use a clear and concise title: Clearly communicating the dashboard's purpose and focus
- Choose the right visualizations: Selecting the most appropriate visualization type for each data set
- Use color effectively: Utilizing color to draw attention, differentiate, and encode data
- Limit the number of visuals: Focusing on key insights and avoiding clutter and information overload

Data modeling is the process of creating a conceptual representation of data structures to support business analytics.
Proper data modeling is crucial for accurate and efficient data analysis, ensuring data consistency and integrity, improved data querying and reporting, and enhanced data visualization and business insights.

Tables represent individual data entities, such as customers or orders.
Columns represent individual fields or attributes within a table.
Relationships define connections between tables to enable data joining and analysis.
Measures are calculated fields that perform aggregations or calculations on data.
Hierarchies organize data into structured categories for easier analysis.

Dashboard design is the process of creating a visual representation of data to support business decision-making.

Clear and concise communication of insights through minimalism and simplicity is essential.
Dashboard design should guide the user through a narrative of key findings and insights, focusing on storytelling.
Interactive and dynamic visualizations enable users to explore and analyze data.
Maintaining a consistent design language throughout the dashboard is crucial.

A clear and concise title should clearly communicate the dashboard's purpose and focus.
Choosing the right visualization type for each data set is essential.
Color should be used effectively to draw attention, differentiate, and encode data.
The number of visuals should be limited to focus on key insights and avoid clutter and information overload.