Data heavily influences the modern world. You can gather, calculate, and tabulate certain data to work out trends and patterns. However, the problem with doing this is that tables are generally uninteresting and often difficult to understand.
For this reason, analysts, professionals, and statisticians use data presentation techniques to present data in formatsthat are morepalpable and appealing to the audience. Statistics show that 90% of the information transmitted to the brain is visual, and 50% of the brain is active in visual processing. These percentages showcase the powerful impact of visual data.
Theoretically, more people understand a particular set of data when it is presented visually through one of the many different types of charts, such as the pie chart, the bar chart, donut charts, or other graphics visualization; rather than when that same data set is presentedin a tabular form.
Whether it is analytics, data points, values, numerical data, or quantitative data, presenting data visually through charts and graphs can look like a cumbersome task at first, depending on how you categorize your data. Nevertheless, if you know the correct way and techniques to present your data, you will find no problem in doing this.
What Are Some of the Most Basic Elements?
Before presenting the actual data in a visual format, it is important to know the basicelements you can use fordata presentation. Here is a list of some of the basic terms:
Indicators are very useful elements in infographics. They provide you with a clear-cut view of how much progress you have made toward achieving a goal. While there are other uses like viewing the value of a particular variable, statisticians mostly use it as a gauge.
They convert these indicator gauges and provide a brief view of how much more you need to work to achieve a particular goal.
However, numerical indicators can simplyinclude a header and a value allowing you to compare previous data. It can indicate whether there was an increase or a decrease, or it canmaintain a stable value.
Line charts are one of themost basicelements.Line charts are particularly popular among businesses because they can display data swiftly and efficiently. It is nearly impossible to misinterpret this data.
Line charts can be used to display different categories of data over the same time period. Different colors are used for the differentcategories being represented;doing this provides clarity over the lines in the graph. You can easily track trends and patterns in the data by analyzing the peaks in the graph.
Often, column chartsare used when you want to compare different categories of data side by side over the same period of time.Column charts provide a more efficient way to look at the changes in the data and figure out how one category differs from the other.
Although these charts cannot conclusively show trends, patterns,or changes over time, they do provide critical analytical information about the data sets that can prove to be helpful.
Furthermore, you can combine a line chart and a column chart to show highlights or contrast significant figures on a graph and analyze an overall trend in the data set.
A pie chart is most certainly an element you have seen before. It might have been in a textbook, an advertisement, or social media. They are very common as they are simple and provide a lot of information without much effort. They are shaped like a circle (or pie shape) with different segments allotted to different categories according to the data.
If a particular category has a higher value than all the other data sets, then that category will be allotted the largest segment in the circle. It is important to remember that pie charts are only effective when you keep the number of categories you include to a maximum of ten.
Scatter plots are commonly used in financial and statistical analyses of data sets. The scatter plots use circles of different colors to represent varying categories visually. And, they also use circles of different sizes to show the volume of data. You can plot them against two variables,and they signify the relationship between the two variables.
These scatter plots are effective in analyzing and identifying trends in the data sets. The scatter plot is applicable and reliable for a smaller data set as it may become too confusing otherwise.
Bubble charts are very similar to scatter plots. They rely heavily on circles and the circumference of the circles to represent data visually. Statisticians commonly use them to show the data element with the highest volume.
The largest circle represents the latest data trends; this provides a lot of insight to where the trends are in the data. However, it is crucial to remember that they take into account only one kind of measurement.
If you wish to quickly extract key figures from the data and perform a comparative analysis of the data set present, then the pivot table is something you should look into. The pivot table might not be the most appealinggraphic, but it is very reliable.
It does, however, lack the ability to provide you with any information on trends in the data. However, you can use these tables for a quick overview and comparison between the different data elements. You can make the pivot tables interactive as well.
An area chart is a perfect tool to use to represent simple data and visualize the changes occurring in the data set. Area charts are similar to line charts; however, area charts also show the area between the lines. The area shown includes numerous colors that effectively differentiate the sets of available data.
You can use area charts to adequately compare two or more data sets by analyzing the difference in the area of the data sets over a particular time set.
Data presentation is an effective way to visualize data and make it readable to others. It also makes representing the data an easier task. You can use any of the elements we mentioned for your infographics or one of the many other visualizations available.