Learn how to make better data visualizations inspired by Storytelling with Data. Discover 10 chart design tips that help you simplify visuals, use color effectively, and communicate insights clearly.

Learn the seven most common data file types every new data analyst should know — including CSV, Excel, JSON, Parquet, SQL, XML, and Feather — and how to open and work with each format.

Master the art of data visuals—learn when to explore insights and when to present them plainly with polished, audience-ready charts.

Transform numbers into compelling narratives. Learn to communicate with clarity, purpose, and impact—even if you're not a data expert.

Avoid misleading visuals. Discover the top charting errors—from chart type choices to misleading scales—and how to fix them fast.

Design visuals that clarify, not clutter. Follow practical steps—from choosing the right chart to simplifying design—for clearer insights.

Build better spreadsheets and dashboards. Learn how dimension and fact tables structure your data clearly—even in Google Sheets or Excel.

We sift through tons of data from different sources to uncover the insights we share in our articles. These 10 steps will help you analyze any dataset with confidence

If you're working with maps, spatial analysis, or location-based data, you'll likely encounter GeoJSON files. In this article, we’ll break down what you need to know about GeoJSON, how to create one, and the tools you can use to open and work with it.

In this guide, we’ll explain the most popular geospatial datatypes and file formats, what they’re used for, what software can open them, and how to choose the right one for your project.

In this guide, we’ll explain what shapefiles are, why they matter, and how to convert a map into a shapefile using simple steps.

Data is stored and exchanged in various file formats. Each format serves a specific purpose, ranging from text storage to complex databases. Understanding these file types, their uses, and the tools required to access them is essential for efficient data handling.

What do you do when you can’t find a dataset for your project? Well, one option is to scrape websites for the data you need. Here’s an example of how it’s done.

Looking for data for your next project? Check out Open Data sources like Statistics Canada, Data.gov, and the CDC for datasets. They’re free to access, reuse, and distribute. Check out the list we’ve assembled.

With a multitude of chart types available, it's essential to match the data's characteristics and the story you want to tell with the appropriate visualization.

Datawrapper is a popular data visualization tool trusted by journalists, educational institutions, finance companies, government institutions, and think tanks. It’s a useful application for those seeking to build interactive, responsive charts, tables, and maps, but have limited coding skills or time.

Books on data science, data analytics, and data visualization are indispensable companions for anyone looking to harness the power of data to make informed decisions in an increasingly data-driven world.

From open government sites to subscription services and everything in between – use this as your go-to reference point when searching for data for your next project.