Data visualization is becoming an increasingly important skill in today’s data-driven world. The ability to take complex data and turn it into an engaging, easy-to-understand visual story is valuable across many industries. From business analysts to designers, having strong data storytelling skills can help make an impact.
But what exactly goes into creating effective data stories? Here, we break down the process into 5 key steps:
Step 1: Understand the Context
The first step is to understand the broader context around your data. Some key questions to ask:
- What is the purpose of this data story? What should the reader learn or take away?
- Who is the intended audience? What visuals and language will resonate with them?
- What background knowledge can you assume they have already? What needs more explanation?
Having a clear purpose and audience in mind will help shape the rest of your decisions as you build the data story.
Tips for Step 1
- Interview stakeholders and intended readers if possible to understand their goals and perspective.
- Consider scenarios of how readers may use or act upon your data story insights.
- Define the specific message or narrative you want to convey based on the context.
Step 2: Wrangle the Data
Next, delve into the data you’ll use to tell the story. Key tasks here include:
- Exploring the raw datasets, noting any issues with data quality or inconsistencies.
- Cleaning and formatting the data so it’s tidy and ready for analysis.
- Combining multiple data sources if needed to get the full picture.
- Filtering or sampling down to the portions of data that support your specific story goals.
Proper data wrangling lays the foundation for visualizing and communicating the insights effectively.
Tips for Step 2
- Use data profiling techniques to scan for anomalies, missing data, outliers, etc.
- Learn any relevant business rules or definitions needed to accurately interpret the data.
- Document your data prep process so it can be repeated or updated in the future.
Step 3: Conduct Analysis
Now we’re ready to dive into some analysis and start uncovering insights. Key tasks include:
- Using statistics and modeling to identify trends, differences, or predictions in the data.
- Summarizing the analysis results and main takeaways in a clear, structured way.
- Focusing on the pieces of analysis that support the specific story you outlined initially.
The analysis should reveal insights tailored to your intended message and audience.
Tips for Step 3
- Choose analysis methods suited for your data types and story goals.
- Check assumptions and validate models to avoid misleading conclusions.
- Outline key numbers, stats, and facts that quantify the main findings.
Step 4: Design the Data Visualization
Now we take the main insights from the analysis and make them visual. Key tasks include:
- Choosing chart types that clearly showcase important findings.
- Designing clean, intuitive visualizations tailored to your audience.
- Formatting elements like titles, labels, legends so the chart is self-explanatory.
- Picking colors, layouts for optimal storytelling and style.
The visuals should make the data easy for readers to absorb and retain.
Tips for Step 4
- Pick charts suited for different data types like time series, rankings, parts of a whole, etc.
- Use basic, familiar charts like bars or lines for general audiences.
- Make liberal use of titles, highlights, annotations to guide attention.
| Chart Type | When to Use |
|---|---|
| Bar chart | Comparing categorical data |
| Line chart | Tracking trends over time |
| Scatterplot | Assessing correlations |
| Pie chart | Showing part-to-whole relationships |
| Histogram | Seeing distribution of numerical data |
Step 5: Tell the Full Story
In this final step, we put together the full data story. Key tasks include:
- Arranging visualizations, narrative text in a logical flow.
- Crafting explanatory text and headers around the visuals.
- Establishing the setting, conflict, resolution from beginning to end.
- Making the takeaways and significance clear to the reader.
The complete narrative should engage readers and allow them to draw their own conclusions.
Tips for Step 5
- Use an inverted pyramid structure – start with key findings and context.
- Break text up with visuals and headers – avoid walls of text.
- Tell a story not just facts – use narrative devices and pacing.
Conclusion
Following these 5 steps can help you take raw data and transform it into compelling, enlightening data stories. First, clearly frame the purpose and audience for the story. Next, wrangle the data into tidy, analysis-ready form. Then, conduct targeted analysis to uncover insights and trends. Design intuitive visualizations that illustrate these findings. Finally, write and organize the full narrative to engage readers and impart impactful conclusions. With practice, you can master the art of visual data storytelling using this process.
