Because of the way our brains process information, using charts and graphs to visualize large amounts of data from different sources is easier than combing through spreadsheets. For example, it’s much easier to see magnitude on bar graphs and trends are more easily visualized via line graphs.
Today, we have modern tools that make it easy to visualize and interact with our business’ data. Instead of relying on spreadsheets to store and access data, today’s programs allow for creativity, making data easier (and faster) than ever to utilize.
There’s value in putting in the extra effort to visualize data
Data visualization massively increases understanding and interaction of data. Unlike when using spreadsheets, visualizing your company's data makes it:
- Easier to explore
- More intuitive
- Easier to explore
By visualizing data, you’re able to quickly identify outliers, trends, and forecasts, making your data more actionable than ever.
Tableau helps you see and understand your data
By using programs like Tableau, you can more quickly identify key data points such as trends and patterns, relative maximums and minimums, and outliers. Instead of spending hours reading spreadsheets seeking notable data, you’re able to see the data points right in front of you.
Learn more about how the structure of your data can make it easier (or harder) to glean business insights. .
In spreadsheets, outliers and mistakes can get overlooked and skew averages, making your data inaccurate. By visualizing your data, it makes it easier to spot potential issues or errors in your data so you’re able to exclude them, identify what is causing them, and eliminate the issue in the future.
Which visualization method is most effective?
There are numerous ways to visualize large amounts of complex data and the question often comes up, “Which visualization method is more effective?”
It comes down to identifying what information you’re looking to derive from your data or what message you’re looking to convey, then selecting the appropriate visualization method.
Distribution is commonly used at the beginning stage of data exploration, usually when looking to understand the variable (either continuous, as in time, or categorical, as in different categories). Both histograms and box-plot graphs are viable vehicles for demonstrating data distribution.
A scatter plot can be an effective way to demonstrate the relationship between two variables. To take this one step further, you’re able to draw a line of best fit to represent the relationship between data points.
Used to compare values across different categories or over time (trends), bar and line graphs are good solutions for visualizing data. When making a comparison across a quantitative variable such as time, it makes sense to use a line graph, whereas visualizing data across different categories is done best in bar graphs.
Used to show the distribution of a variable across categories, understanding data composition is best done via pie or bar charts. In these visualizations, variables are typically denoted by the use of different colors.
Make data-driven decisions
Data-driven decisions can be immensely impactful in moving your business forward. By visualizing your data, you’re able to share your findings with your team more easily, allowing you to make data-driven decisions for your organization.
Reviewing your visualized data as a team can allow you to identify opportunities for improvement within the organization, increasing efficiencies, improving the bottom line, and more.
Is your business making data-driven decisions? Doing so can increase efficiencies and uncover opportunities for business growth. Grab this guide to get started.