One of the most useful tools available for presenting complicated material in an accessible way is data visualization. This rapidly evolving field is focused on using visual representations like graphs or charts to convey raw data. Presenting data in a visual manner makes it easier to understand and faster to process, even for those who aren’t mathematically inclined or trained in analytics. These visual representations of data aren’t just visually appealing, they also tell a story about the information, allowing audience members to spot outliers, notice trends, and see patterns emerge from data. Visually conveying points is a powerful way to leverage data in order to achieve the desired outcome.
What is Tableau?
Tableau is the fastest-growing platform for visual analytics available on the market. It allows users to simplify raw data into a format that’s easy to access and understand by those working at any level of an organization. Even non-technical Tableau users can create customized dashboards and worksheets with the help of this versatile tool. It’s relied on by teachers, students, Data Scientists, Analysts, executives, and business owners for their end-to-end analytics needs. For these reasons, Tableau is considered to be the leading analytics platform for business intelligence.
In 2003, Tableau was created as a way to improve analysis flow and use visualizations to make data more accessible. This value continues to inform Tableau’s evolution. Currently, Tableau offers a complete and integrated platform for data analytics. It provides its users with the necessary resources to help them thrive in a data-driven culture. Some of Tableau’s most remarkable features include its capacity for data blending, real-time analysis, and data collaboration. Because Tableau does not require programming skills or technical expertise to operate, users of all backgrounds can easily work with this software. It can be installed directly onto one’s hardware from a web download and be operational in just twenty minutes.
The Tableau product suite is used by many companies, like Skype, Wells Fargo, Nike, and Coca-Cola, for data visualization. In fact, thousands of companies and organizations use Tableau for their data analytic and visualization needs.
Kinds of Charts that can be Created Using Tableau
Once Data Analysts or Data Scientists have collected data and asked questions about the data, they must then choose the most effective visual method to present their findings to their target audience. Tableau provides users with a variety of graph chart types, some of which are more appropriate than others for certain types of data.
The following list contains some of Tableau’s most popular graph and chart types, as well as a brief description of the situations in which they are applicable:
- Line charts, also known as line graphs, connect data points to one another in order to display the data’s evolution. This kind of chart provides a clear way to depict data trends that occur over time, such as how many views a website has had during November. Line charts offer a clear and straightforward representation of the changes in a specific value, as well as how these fluctuations relate to one another.
- Pie charts are often used as a supplementary chart type in Tableau. Since pie charts alone cannot provide an accurate snapshot of the data because the user must create a context in which to view the chart, relying on just a pie chart for visualizations can result in the audience missing crucial data. This is why pie charts are often used as a supplement to other visualizations being depicted in Tableau.
- Scatter plots are commonly used to explore how different variables relate to one another, as well as to determine if variables change independently of one another, or if one variable can be used to predict another. Scatter plots are effective at displaying a variety of distinct data points, all in one place.
- Maps have a variety of uses when creating visualizations. They are particularly helpful for displaying location-specific information, such as country names, postal codes, or state abbreviations. Maps can also be used to clearly indicate the correlation between location and data trends.
- Density maps are a kind of Tableau map that are used to highlight concentrations or patterns that may not be noticeable using other visual display options where overlapping elements are present. They provide an effective option for users who wish to visually depict data with numerous data points in a relatively small geographical area.
- Symbol maps are a kind of chart that use quantitative values to stand for map locations using symbols. Symbol maps provide users with a helpful way to visually display geographical data via longitude and latitude. A mark is used to draw attention to the specified coordinates.
- Bubble charts are not a distinct visualization type, but are typically used to add details to maps or scatter plots in which the relationship between at least three measures is being depicted. In bubble charts, large volumes of data can be presented in a visually clear and engaging way by depicting it with circles in different colors and sizes.
- Treemaps are a helpful tool for those who wish to relate one data segment to the whole. Within a treemap, each rectangle is split into smaller sub-branches that use space to visually depict the percent of the total for various categories.
- Pareto charts are a sort of bar graph used to illustrate significant situations. Each value on a Pareto chart is displayed in descending order by bars (longest bars on the left and shortest on the right), and the line stands for the ascending cumulative total.
- Text tables provide a basic way to depict data via columns. They are also known as cross-tabs or pivot tables.
- Histograms function similarly to bar charts, but groups values into continuous ranges. Histograms are applicable in situations in which continuous data on an interval scale must be summarized. This graphing tool depicts the significant features of the data distribution.
- Gnatt charts are created to show the schedule of a project, or any changes in a given activity during a specified time period. These charts also provide information on the necessary steps to complete before other phases of a project can begin, so that resources can be allocated accordingly.
- Heatmaps use color to depict data. They have a variety of applicants in data analytics but are often used to depict user behavior on a given website. Heatmaps can provide valuable insights into metrics such as how far users scroll down on a page, as well as where they click on a website.
- Waterfall charts are one of the more complex charts in Tableau. They illustrate the cumulative effect of positive and negative values in a sequence. Waterfall charts provide an effective means to illustrate how a starting value (such as a checking account balance), eventually becomes a final value (the value on the last day of the month) by incorporating a set of intermediate additions and subtractions.
With the help of these charts and graphs, as well as others, Tableau users have a range of powerful graphing tools available to help present their data in a visual, engaging, and interactive manner that’s best suited to the needs of their audience.
Hands-On Tableau & Data Visualization Classes
Are you interested in learning more about how to create stunning and helpful data visualizations? If so, Noble Desktop offers Tableau classes that are designed to prepare students to work with this industry-standard data visualization software.
Noble Desktop’s data analytics classes are open to students with no prior coding experience. These full-time and part-time courses are taught by top New York Data Analysts and provide timely and hands-on training for those wishing to learn more about topics that extend beyond data visualization, such as Python, SQL, Excel, or data science, among others. In addition, Noble’s live online data visualization courses are designed for students who prefer learning in the virtual format.
Noble Desktop’s Classes Near Me tool is designed for those who want to locate other data visualization courses in the area. These courses provide training for those who are new to working with data, as well as those with prior experience who hope to perfect their data visualization skills.