It’s no secret data is powerful – when you actually know how to use it.
But with so much data to sift through, it’s not easy to get clear takeaways from raw data spreadsheets. We comprehend data much better through pictures. That’s where data visualization comes in.
In this guide, we’ll make data visualization easier to understand. Our goal is to leave you feeling a lot smarter and ready to visualize your own data like a champ.
So, let’s get started.
- What is Data Visualization?
- ‘A Picture is Worth a Thousand Words’
- What are the Benefits of Data Visualization?
- Data Visualizations Types
- Top 5 Data Visualization Tools for 2023
- Data Visualization Best Practices
What is Data Visualization?
Data visualization is a fancy term for the graphical representation of information and data. It shows data in a visual context, such as a chart or a graph, to enable anyone viewing it to better understand the significance of that data.
‘A Picture is Worth a Thousand Words’
Data visualization is important because it allows us to better understand, internalize, and analyze large amounts of data.
The brain is programmed for visualization. That’s why we are capable of quickly identifying orange from black, circle from triangle, the brick pattern on a building. Data visualization enables us to quickly scan a graph or a chart and discover patterns, trends, and outliers.
We are visual beings and data visualizations are the single easiest way for our brains to receive and interpret shiploads of information.
What are the Benefits of Data Visualization?
Data visualization brings data to life.
It allows us to recognize relationships and patterns between data, and give it greater meaning. It helps us identify factors affecting consumer behavior, pinpoint areas needed for improvement, understand product placement, manage inventory, predict sales, improve productivity, etc.
Here’s a list of the most important benefits of data visualization:
- Makes data easy to digest and more memorable
- Quick and better data analysis
- Helps in identifying patterns, trends, and outliers easier
- Allows for data-driven decision making
- Empowers data story-telling
- Enables quick action
Data Visualization Types
We’ve come to the most flavorful section of this guide. Here’s we’re going to lay out the most common types of data visualizations. This section will help you gauge which type of chart or graph is right for your data.
Pie charts or graphs show the relationship between parts or percentages of a whole. They make it easier to see whether different data points combine together to be larger than another. Pie charts are commonly used in business to show percentage of revenue from different products, profit from different countries, number of units sold per product, customer demographics, etc.
Doughnut charts are similar to pie charts, but offer space in the center for more information.
Line graphs show a series of data points connected by a line. Their main goal is to show how data changes over time. Line charts are often used to describe how revenue changes from quarter to quarter, how many new customers were acquired month-to-month, and how employee productivity varies year to year.
An area chart is an extension of a line graph. The difference is that the area between the baseline and data points plotted on the line is filled with color.
Also called bar charts, use bars to represent data. This is one of the most frequently used types of graphs. Similar to pie charts, bar charts are very simple to read. They can be horizontal, vertical, stacked, and grouped. Bar charts are great when we want to track one or two data points over a period of time.
A pyramid chart is used to represent different levels. Because of its pyramid shape, each level is unique in size and importance. These types of charts come in handy when you need to visualize hierarchical structure, as well as quantity or size.
Tables are smaller spreadsheets that show various data points in rows and columns. They are great to display pricing options, comparative features, competing product benefits, and more.
A dashboard is a collection of different visuals showing important metrics and KPIs all in one place. Like a car’s dashboard, data dashboards organize and display information from multiple sources in one location. Dashboards help you visualize and drill down trends and patterns in your data in order to answer questions and make better decisions. Contact Data Factory if you need help building an interactive dashboard for your business.
Top 5 Data Visualization Tools for 2022
With so many data visualization tools available, from free versions to pricey feature-rich platforms, how do you choose the right solution for your business?
Here’s a list of questions you should keep in mind before you select a data visualization tool:
- What am I trying to accomplish?
- What features do I need?
- What’s my budget?
- Where is my data coming from?
- Where will I publish my visualizations?
Once you answer these questions, here’s a list of the top 5 data visualization tools:
- Microsoft’s Power BI
Power BI, our personal favorite, is a business intelligence (PI) tool that lets you visualize your data and share insights across your business, or integrate them in your app or website. It’s one of the most complete data visualization tools available on the market.
Competitively priced, with Power BI you can create stunning visualization and deliver real-time insights for fast decision making. Power BI integrates with many Microsoft products and cloud services, making it a versatile solution for businesses. If you’re familiar with Excel, you won’t have to work too hard to understand Power BI.
Pros: competitively priced | high performance | easy to learn if you know Excel | syncs with Facebook, Oracle, Google Analytics and many more | user-friendly interface | free plan available
Cons: desktop version not compatible with Mac
Tableau is a data visualization and analytics platform that allows users to explore data and share insights. It’s easy-to-use, flexible and powerful. Tableau allows you to build beautiful visualizations with a drag and drop feature.
Pros: high performance | integrates with Slack
Cons: steep learning curve | requires some SQL knowledge | priced higher than competitors
Looker, offered by Google, is a powerful business intelligence tool that allows you to see your data in a stunning variety of visualization types, thanks to its plugin database. It offers user-friendly workflow and is completely browser-based.
Pros: plugin marketplace for various visualization types | drag-and-drop interface | excellent support chat
Cons: lack of flexibility | too much data can slow it down
- Qlik Sense
Qlik Sense is a data visualization software that supports a wide range of analytics use cases across the life-cycle from data to insights. It uses artificial intelligence (AI) to help users comprehend and analyze data better. Qlik Sense offers a user-friendly interface for users to create interactive data visualizations.
Pros: drag-and-drop interface | AI insights
Cons: priced higher than competitors | steep learning curve
- Zoho Analytics
Zoho Analytics is a powerful, cloud-based business intelligence solution that enables you to import data from a variety of sources and design insightful dashboards for your business. It can be used in multiple departments including sales, marketing, HR, finance and operations. Zoho even offers a free plan.
Pros: drag-and-drop interface | free plan availabl
Cons: too much data can slow it down | user interface needs improvement
Data Visualization Best Practices
Now that you’re armed with data visualization knowledge let’s add best practices on top.
- Know your audience(s)
The first and most important consideration to creating engaging and helpful data visualization is knowing your audience. You want to ensure your audience has the capacity to interpret the charts and graphs presented. You need to consider their needs, skills, knowledge, and goals.
- Pick the right visual type
The second most important is choosing the right graph/chart for the data you want to present. Your audience should be able to tell a story by looking at your visualization.
- Less is more
Data visualizations need to be easily digestible and simple. Avoid overdressing your data visualizations with unnecessary elements.
- Titles matter
Use effective titles to help the viewer quickly understand the information.
- Use colors effectively
Color is important. It can tell data stories on its own. You should use color to highlight and emphasize important information. However, too much color can be confusing. Keeping it simple is the best way to go.
- Avoid too much text
Too much text can be distracting and can make your data visualization difficult to understand. When you use text, make sure it highlights important information only.
Ready to Visualize Your Data Today?
Data visualization is for everyone, not only for data scientists. Teachers, marketers, coaches and everyone else in between uses data visualization.
Creating an impactful data visualization requires careful planning, attention to detail, and an eye for design. Keep this guide in mind when building data visualizations for your business.
If you don’t feel confident enough to create your own data visualizations, try out Data Factory. Our team of data analysts has the skills and experience to help you build beautiful, interactive data visualizations for your business.
Regardless of who you work with, data visualization is an extremely important aspect of your business and you need it implemented asap!