We’re still teaching math like it’s 1895: formulas, drills, and test scores, while the world runs on data. Discover why it's not just a math gap, but a thinking gap, and what today’s students really need to thrive in a data-driven future.
The Boston Celtics are losing not because they ignored analytics, but because they used them without context. This article explores the danger of blindly following data and the critical difference between being data-driven and truly data-literate.
AI is changing how we think—but have our thinking skills kept up? Discover the four mindset shifts that will set modern professionals apart in an AI-powered world.
Answer the questions to find the most appropriate visualization for your data If you want a simpler page that shows all visualizations on a single page and you can filter to visualization goal, data types, and number of variables, click here
What's your primary visualization goal?
What type of comparison?
What are your data characteristics?
How many categories?
How are the variables related?
What's your time data like?
How many series are you comparing?
What's your comparison focus?
What type of target comparison?
What's your target type?
How are targets related?
What aspect of distribution?
What's your data type?
What's the distribution shape?
What's your focus?
How many variables?
How many distributions?
How many groups?
What type of relationship analysis?
What types of variables are you analyzing?
What's your measurement scale?
How many categories?
How many levels in each category?
How many variables are you analyzing?
What type is the third variable?
What type is the fourth variable?
Are the variables related?
What type of clustering?
How many dimensions?
What's the hierarchy type?
What's the density measure?
What type of composition analysis?
How many parts are you showing?
What's your focus?
Are parts grouped?
What's the scale type?
What's the time scale?
How many time points?
What's the focus?
What's the period?
How many levels in the hierarchy?
What's the focus?
Is space constrained?
What's the connection type?
What type of temporal analysis?
What type of data?
What's the frequency?
What's the interval?
What's the accumulation?
What type of cycle?
How many cycles?
What's the nesting?
How do cycles relate?
What type of comparison?
How many points?
What's the period type?
How many groups?
What type of anomaly analysis?
How many variables?
What's the distribution?
What's the relationship?
Are variables related?
What type of pattern?
What's the baseline?
What's the periodicity?
What's the sequence type?
What type of grouping?
How many groups?
How many levels?
What's the clustering?
Recommended Visualization
Are You Data Literate?
Becoming data literate begins in your inbox. Sign up to receive expert guidance, news, and other insights on the topics of data literacy and data-informed decision-making. Want to know more about our mission? Visit our About Page. Thanks for visiting!