Excel is a common data visualization tool. This popularity is due, in large part, to its intuitive functionality and ability to handle large data. It offers a variety of quick and efficient ways to store, clean, and visualize data in one convenient environment. In particular, "pivot tables" allow the user to visualize thousands of records, in real time, with only a few mouse clicks. The popularity of Excel stems also from it's broad compatibility with other visualization software. If you're looking for a powerful, efficient, and broadly compatible environment to work with data then Excel may be the correct choice.
Learning Tools
Reading
Storytelling with Data by
Don't simply show your data--tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples--ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data--Storytelling with Data will give you the skills and power to tell it!
Storytelling with Data by
Influence action through data! This is not a book. It is a one-of-a-kind immersive learning experience through which you can become--or teach others to be--a powerful data storyteller. Let's practice! helps you build confidence and credibility to create graphs and visualizations that make sense and weave them into action-inspiring stories. Expanding upon best seller storytelling with data's foundational lessons, Let's practice! delivers fresh content, a plethora of new examples, and over 100 hands-on exercises. Author and data storytelling maven Cole Nussbaumer Knaflic guides you along the path to hone core skills and become a well-practiced data communicator. Each chapter includes: ● Practice with Cole: exercises based on real-world examples first posed for you to consider and solve, followed by detailed step-by-step illustration and explanation ● Practice on your own: thought-provoking questions and even more exercises to be assigned or worked through individually, without prescribed solutions ● Practice at work: practical guidance and hands-on exercises for applying storytelling with data lessons on the job, including instruction on when and how to solicit useful feedback and refine for greater impact The lessons and exercises found within this comprehensive guide will empower you to master--or develop in others--data storytelling skills and transition your work from acceptable to exceptional. By investing in these skills for ourselves and our teams, we can all tell inspiring and influential data stories!
Effective Data Visualization by
This comprehensive how-to guide functions as a set of blueprints--supported by research and the author's extensive experience with clients in industries all over the world--for conveying data in an impactful way. The book covers the spectrum of graph types available beyond the default options, how to determine which one most appropriately fits specific data stories, and easy steps for making the chosen graph in Excel. Available with Perusall--an eBook that makes it easier to prepare for classPerusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.
Different flavors of Tableau:
Learning Tools
Tableau tutorials and training can be found on the official Tableau website as well as through Lynda.
Official Tableau Resources:
Misc:
Reading:
R is a free programming language and environment that can be used to create visualizations and perform statistical computing. It is extremely versatile with respect to the types of visualizations that can be made and the manipulation of datasets. Though it may be initially less intuitive than other visualization means, it compensates by rewarding the user with a near endless selection of packages that make cleaning and visualizing data immensely customizable. It's longstanding popularity with researchers, academics, and businesses is a testament to it's utility in numerous contexts. If you want to clean and visualize your data in one place, with practically limitless customization, then R may be the right tool for you.
Get R
Download R (Programming Language): https://cran.case.edu/
Download RStudio (IDE): https://www.rstudio.com/
Learning Tools
Reading:
R for Data Science by
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle--transform your datasets into a form convenient for analysis Program--learn powerful R tools for solving data problems with greater clarity and ease Explore--examine your data, generate hypotheses, and quickly test them Model--provide a low-dimensional summary that captures true "signals" in your dataset Communicate--learn R Markdown for integrating prose, code, and results
Python is a free, general purpose, and high level programming language that can be used to create data visualizations. Python offers near limitless varieties of visualization capabilities. It is a language that is extremely common across academia and industries. Because it is so common, it is a good choice if you want to integrate visualizations into pre-existing applications. If you have a programming background and are looking for a highly versatile way to visualize data, then Python may be a good option for you.
Learning Tools:
© The Ohio State University - University Libraries
1858 Neil Avenue Mall, Columbus, OH 43210
Phone: (614) 292-OSUL (6785)
If you have trouble accessing this page and need to request an alternate format, contact the webmaster.
