Data visualization, how to use Google Data Studio
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Data visualization strategy
How to view complex performance measurement data at a glance and use Google Data Studio to automate reports
We will teach you data visualization, how to use Google Data Studio, and report automation strategies.
Data visualization core strategy
1. Select chart type
Select a chart type that matches the characteristics of your data.
- bar chart
- line chart
- pie chart
- heatmap
2. Color and design
Apply intuitive colors and designs.
- color palette
- brand color
- Consider accessibility
- Stay consistent
3. Filters and dashboards
Allows users to easily filter the data they want.
- date filter
- dimension filter
- Dashboard configuration
- interactive elements
4. Mobile optimization
Optimized to look good even in mobile environments.
- Responsive Design
- Touch Optimization
- Improved readability
- loading speed
5. Share and collaborate
Make it easy to share data and collaborate with team members.
- share link
- Permission settings
- Real-time updates
- Comment function
6. Automation
Increase efficiency by automating data visualization.
- automatic update
- Scheduling
- Notification settings
- Generate report
Compare data visualization tools
| tools | Difficulty level | cost | function | collaboration |
|---|---|---|---|---|
| Google Data Studio | middle | free | high | high |
| Tableau | high | high | very high | high |
| Power BI | middle | middle | high | high |
| Excel | low | middle | middle | middle |
| Python | high | free | very high | low |
| R | high | free | very high | low |
5 steps to building data visualization
Step 1: Requirements Analysis
Analyze your data visualization needs.
- goal setting
- custom
- data source
- Functional Requirements
Step 2: Prepare your data
Prepare the data needed for visualization.
- data collection
- data cleaning
- data conversion
- Data Verification
Step 3: Design the visualization
Create a design to visualize your data.
- Select chart
- layout design
- color selection
- interaction design
Step 4: Implementation
Implement designed visualizations.
- Select tool
- implementation
- test
- Optimization
Step 5: Deploy and Maintain
Deploy and maintain visualizations.
- distribution
- User training
- monitoring
- continuous improvement