Data storytelling

Data Visualization in Databricks

Gang Wang

Senior Data Scientist

What is data storytelling?

Crafting narratives from data
Combining insights with visualizations

Purpose:

Make complex data accessible
Engage and inform your audience

Why it matters:

Transforms raw data into insights
Enhances decision-making

Conceptual illustration of data storytelling

¹ Pictures: AgencyAnalytics

Before: showing data

Cluttered line chart, difficult to interpret
Raw data without context

After: storytelling

Clear narrative highlighting key insights
Simple bar chart emphasizing important data points

¹ Pictures: Storytelling with Data

The role of data visualizations in storytelling

Bar charts: compare quantities across categories

Bar chart

Line charts: show trends over time

Line chart

¹ Pictures: Corporate Finance Institute, Storytelling with data

Pie charts: display proportions and part-to-whole relationships

Pie chart

Scatter plots: show relationships and correlations

Scatter plot

¹ Pictures: GeeksforGeeks, Math is Fun

Heat maps: reveal patterns and intensity of data

Heat map

Histograms: show the distribution of numerical data

Histogram

¹ Pictures: Sage Research Methods, Stata

Area charts: highlight changes over time with stacked data

Area chart

Understanding statistical distributions

Why they matter

Reveal patterns in data
Highlight central tendencies: mean, median, mode
Show spread: range, variance, standard deviation
Identify shape: skewness, kurtosis

central tendencies

¹ Pictures: Medium

Creating Customizable Tables

Purpose of Customizable Tables:

Tailor presentation to specific needs
Highlight key insights clearly

Key features:

Formatting options
Column and row adjustments
Sorting and filtering
Data labels

Conceptual illustration of Customizable table

¹ Pictures: UX Collective

Let's practice!

Data Visualization in Databricks

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