17 Data Visualization Resources You Should Bookmark

Data Visualization Resources: The Ultimate Guide for 2024

Data is everywhere these days. But to make sense of it all, you need data visualization. Visualizations transform raw facts and figures into accessible, engaging graphics that allow for new levels of understanding and insight.

Whether you‘re a marketer aiming to create more persuasive content, a business analyst uncovering key trends, or a data scientist making new discoveries, data visualization is an indispensable skill. The right visualization can simplify the complex, reveal the unexpected, and influence decisions.

But where do you start? While spreadsheets like Excel can create basic charts and graphs, today‘s data visualization tools go far beyond. They range from simple drag-and-drop builders to advanced programming libraries for creating custom data visualizations and dashboards.

In this guide, we‘ve rounded up the best data visualization resources for 2024, including:

  • Different types of data visualizations and when to use each
  • Tools for finding, cleaning and preparing your data
  • Top data visualization tools, both free and paid
  • Examples of inspiring data visualizations
  • Tips for creating compelling data visualizations
  • Emerging visualization trends to know for 2024 and beyond
  • Resources for learning and keeping up with data visualization

No matter your skill level, you‘re sure to find something useful here to take your data viz to the next level. Let‘s dive in!

Types of Data Visualizations
Before we get into the tools, let‘s cover the main types of data visualizations:

  • Charts: bar charts, line charts, pie charts, scatter plots, bubble charts, etc. Great for showing comparisons, distributions, trends over time, and relationships between variables.
  • Graphs: flow charts, network diagrams, hierarchical tree diagrams, etc. Ideal for representing flows, connections and structural relationships.
  • Infographics: combining charts, graphs, text and images to tell a visual story. Engaging format for presenting key facts and figures.
  • Dashboards: collections of visualizations displaying real-time data from multiple sources. Provides an at-a-glance overview of key metrics and performance indicators.
  • Maps: Displaying geographic data as color-coded regions, points, routes, flows, heatmaps etc. Powerful way to see spatial patterns and trends.
  • 3D, VR, AR: Three-dimensional, virtual and augmented reality visualizations for immersive data experiences. Emerging area with exciting potential.

The type of visualization you choose depends on the kind of data you have, the message you want to convey, and your audience. In general, aim for something clear, focused and visually engaging that viewers can grasp quickly.

Finding and Preparing Data
Of course, the first step in data visualization is obtaining some data. You may already have data on hand, but if you‘re looking for public data to visualize, here are some great sources:

  • Government open data portals
  • Google Dataset Search
  • World Bank Open Data
  • Kaggle datasets
  • Socrata Open Data Exchange
  • Data.world
  • Reddit r/datasets

Once you have your data, you may need to do some cleaning and preparation before visualizing it. This could include reformatting data types, handling missing values, merging datasets, deriving new variables, aggregating and summarizing, or doing statistical analysis and machine learning. Some popular tools for data wrangling include:

  • Excel Power Query
  • Google Sheets
  • OpenRefine
  • Trifacta Wrangler
  • Tableau Prep
  • Python libraries: Pandas, NumPy, Dplyr
  • R libraries: Tidyverse, data.table

Top Data Visualization Tools
Now for the fun part – creating the visualizations! Here are some of the best tools to try, ranging from beginner-friendly to advanced:

  • Microsoft Excel – The reliable spreadsheet standby. Can create basic charts and graphs. Free with Microsoft 365.
  • Google Sheets – Free, web-based spreadsheet. Similar charting capabilities to Excel.
  • Canva – Popular online design tool with an infographic maker. Free and paid plans from $12.99/month.
  • Visme – Another online infographic and chart maker. Free and paid plans from $15/month.
  • Infogram – Web-based tool for creating interactive infographics and reports. Free and paid plans from $19/month.
  • Piktochart – Easy infographic builder with templates. Free and paid plans from $24.17/month.
  • Tableau – Powerful data analysis and visualization software. Free Tableau Public plan, paid plans from $70/user/month.
  • Looker – Web-based BI and data visualization platform. Contact for pricing.
  • Microsoft Power BI – Business intelligence and visualization tool. Free Power BI Desktop, paid Power BI Pro from $9.99/user/month.
  • Qlik – End-to-end data integration and visualization platform. Contact for pricing.
  • D3.js – Popular open-source JavaScript library for custom interactive visualizations. Free.
  • Chart.js – Simple yet flexible JavaScript charting library. Free and open source.
  • Plotly – Open-source library for interactive web-based visualizations. Free and paid plans.
  • Python plotting libraries: Matplotlib, Seaborn, Plotly, Bokeh. Free and open source.
  • R visualization packages: ggplot2, plotly, highcharter, rbokeh, leaflet. Free and open source.

Many of these tools also offer built-in data connectors so you can hook your visualizations up to live data sources. Embedding visualizations in webpages, apps and dashboards is also supported.

Inspiring Visualization Examples
Need some inspiration for your own visualizations? Check out these examples of data viz done right:

[Insert 4-5 images of impressive data visualizations. For each image, add a caption explaining what makes it effective – e.g. creative chart type, great use of color, tells a compelling data story, interactive elements, etc.]

Tips for Creating Great Visualizations
Creating effective data visualizations is a combination of art and science. Here are some guidelines to keep in mind:

  1. Know your audience. Who are you creating this for and what do they need to know? Let that shape your decisions.
  2. Choose the right visualization for your data and message. Avoid the temptation to use overly complex or flashy types just because they look cool. Stick with tried and true charts when appropriate.
  3. Keep it simple and clutter-free. Don‘t try to cram too much into one graphic. Focus on the key message you want viewers to take away.
  4. Use color purposefully, not decoratively. Color draws the eye and connotes meaning, so be intentional. Use palettes that are colorblind-safe and work for both light and dark modes.
  5. Make text clear and easy to read. Avoid fancy fonts and use proper text sizes and colors. Don‘t make people squint!
  6. Enable people to explore the data themselves. Interactive elements like filtering, sorting, drill-downs, and tooltips help viewers find their own insights.
  7. Provide context. Title, label and annotate your visualizations so people understand what they‘re looking at. Explain any methodology or data sources.
  8. Tell a story. The best visualizations take you on a journey from "what" to "so what". Craft a compelling narrative with your data and people will keep coming back for more!

Visualization Trends for 2024 and Beyond
Data visualization continues to evolve at a rapid pace. Here are some key trends to watch:

  • Interactive and animated visualizations that respond to user input
  • AI and machine learning tools that automatically find insights and suggest best visualizations
  • Immersive data experiences through virtual and augmented reality
  • Real-time streaming visualizations of constantly-updating data feeds
  • Collaborative data visualization and storytelling tools for teams
  • Code-free tools enabling business users to build their own visualizations
  • Data viz meets data art – Creative blends of analysis and aesthetics

Learning and Inspiration Resources
Want to learn data visualization and keep growing your skills? These resources will set you on the right path:

  • Courses: Coursera, EdX, Udemy, and Datacamp all offer courses in data viz tools and techniques. Flowing Data and The Pudding have tutorials focused on D3.
  • Books: Storytelling with Data by Cole Knaflic, The Visual Display of Quantitative Information by Edward Tufte, The Big Book of Dashboards by Steve Wexler and Jeffrey Shaffer
  • Podcasts: Data Viz Today, Data Stories, Storytelling with Data
  • Blogs: Flowing Data, Information is Beautiful, The Pudding, The Atlas, Visualizing Data
  • People to follow on Twitter: Alberto Cairo, Nadieh Bremer, Mike Bostock, Moritz Stefaner, Shirley Wu, Lisa Charlotte Rost
  • Conferences: Tapestry Data Storytelling Conference, OpenVisConf, Information+ Conference, Malofiej Infographics World Summit, IEEE VIS

Equipped with these resources, you‘ll be well on your way to creating data visualizations that engage, inspire and drive results. So go forth and viz!