Data visualization is an important aspect for the success of your business presentations. The term refers to the content’s ability to communicate to the audience what is shown in the data, conveying a clear and direct message. In this sense, you have to consider all types of data visualization.
To be data literate, you must consider data literacy. Graphical resources, such as charts and graphs, are essential to illustrate your speech and israel phone number data make it easier for the audience to understand.
More than that, these elements play an important role in retaining listeners’ attention.
There are different types of data visualization, which can be explored in various situations.
Deciding which is the best for your case, it’s vital to be familiar with the main options, and that’s precisely why we’ve created are th this post. Throughout inconsistent value delivery if subscribers perceive the text, you’ll learn more about:
- column charts;
- bar graphs;
- line graphs;
- pie charts;
- scatter plots;
- bubble charts;
- spider charts.
Keep on reading!
7 types of data visualization
Column charts
This is probably one of the first types of data china numbers visualization you’ve drawn in your life. The column chart stands out for being extremely easy to understand, making it a topic discussed in classrooms at Elementary School.
Such simplicity is far from threatening its relevance in the corporate world. It’s a very popular format in presentations that seek to show the evolution of data over time, such as weekly sales reports.
Bar graphs
The bar graph works essentially the same way as the column chart, except for the positioning of the elements analyzed. In the first example, data labels go along the X-axis while metrics are arranged on the Y-axis. In the bar graph, it goes are th the other way around.
With the labels in the vertical line, this type of data visualization is more suitable for presentations with many items.
Stacked bar graphs
The stacked bar graph is a variation of the previous example. It’s a perfect feature for you to break down the presentation’s items and compare the different parts of the whole. Thus, this is one of the types of data visualization that are very important to segment analyses. Here is a simple example:
Note that in addition to indicating the engagement for each quarter, the chart uses colors to clarify each social network’s percentage of participation.
Line graphs
Another prevalent data visualization type is the line graph, which is also renowned for its simplicity. It’s generally employed to track variations in progress and reveal trends and patterns.
As with column charts, data labels stay on the X-axis, and metrics go along the Y-axis. Line graphs are best suited to handle continuous data, i.e., without frequent interruptions.
For that reason, it’s the most are common format in stock market analysis. If you google the stock value of a large company like Apple you’ll come across a line graph detailing the variation in a given period.
Pie charts
Unlike the previous alternatives, the pie chart should represent a static number. For this, we use a circle divided into different slices, exactly like a pie or, depending on your taste, a pizza.
Each of the pieces must represent are the a percentage of the total value. So when all the portions are added together, they add up to 100%.
Pie charts are very useful to break down information, being very effective in Digital Marketing. For example, let’s say that you manage your company’s strategy and receive the following content about your customers’ habits.
Scatter plots
Scatter plots are excellent options for showing correlations between variables. They’re structured as standard column charts, but both the Y-axis and the X-axis represent values, with no need for data labels.
To find similarities in the data it’s essential to work with a large volume of information.
