Data Storytelling is that art of translating complex data analyses and insights into easy-to-understand narratives. It essentially involves crafting a story that communicates the key findings from the data. The major goal here is to make data more engaging and actionable for a broader audience.
Here are some of the data stories to tell;
- Change Over Time ?? Tracking performance progression over the past, present, and future. An example would be tracking how the popularity of a certain politician has changed over time
- Drill Down ?? Going to a more granular level of the data, drilling down goes into the more specific cases making us understand why a distribution of the data is the way it is.
- Zoom Out ?? This is the inverse of Drill down. Zooming out therefore explains how something affects the bigger picture.
- Contrast ?? Contrast shows the difference or variations between categories, it draws attention to a specific aspect of the data, making a narrative easier to understand. When contrast is properly incorporated it gives more clarity to the audience.
- Point of Intersections ?? It shows how seemingly unrelated categories relate. Digging deeper into intersections gives a more nuanced understanding of relationships within the data
- Dissecting the Factors ?? Factors are basically variables/elements that influence the outcomes or trends seen in the data. Understanding the key factors helps in providing the context, explaining patterns and drawing meaningful conclusions.
- Outliers ?? Outliers are the data points which deviate from the mean. They in most cases arise from poor quality data or might be due to an anomaly that needs to be explained some more.
