Data Fluency & Insight
Data Visualization with Excel & Power BI
Choose the right chart and build clear visuals in Excel and Power BI that support better decisions.
Standard version
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This course equips participants with the skills to transform raw data into clear, compelling visuals that drive understanding and better decision-making. Learners explore visualization principles, chart selection, design best practices, and hands-on techniques in Excel and Power BI to communicate insights with clarity and impact.
What you'll learn
- Explain the purpose and principles of effective data visualization
- Select the right visual based on data and message
- Apply design and formatting best practices to improve clarity and usability
- Build and customize visuals in Excel and Power BI
- Communicate insights clearly using visual analytics techniques
What you'll be able to do
- Translate raw data into meaningful visual insights
- Choose the appropriate visual type for trends, comparison, and relationships
- Use Excel charting, conditional formatting, and dashboard elements
- Create basic interactive reports and visuals in Power BI
- Apply ethical and accessible data visualization standards
Leaders make better decisions when data is presented clearly. This course helps federal employees turn raw data into visuals that communicate insights quickly and accurately. Participants learn visualization principles, choose the right chart for each message, and apply design best practices in both Excel and Power BI.
What you'll learn
- Explain the purpose and principles of effective data visualization.
- Select the right visual based on the data and the message.
- Apply design and formatting best practices for clarity.
- Build visuals in Excel and Power BI.
- Avoid visuals that mislead or confuse.
What you'll be able to do
- Create charts that make data easy to understand.
- Choose the right visual for each message.
- Present data clearly to leadership and stakeholders.
- Build visuals in the tools their agency uses.
- Avoid common visualization mistakes.