Why Do We Visualize Data?
There is a lot of talk about data today, many things are being told. However, each data has a story that the data group actually hides within itself. The main thing is to be able to decipher the story hidden behind this data and to tell this story to different people. I see discovering the story of the data as a separate event, and being able to tell people by drawing meaningful conclusions as a result of this story as a different event. In this blog post, I will tell you why we are presenting this through visualization while telling people about the data.
The Importance of Visualization
In your work or school life, you have often made presentations within the scope of your projects or a report. These presentations can often be a nightmare for many people. It is necessary to consider many criteria such as how the amount of writing in the presentation will be, how the harmony between the visuals and the intended explanation will be adjusted.
The point I want to reach from here is this; In these presentations, it is necessary to present the event to them in the most understandable way without drowning and boring the audience. Here, the importance of visualization comes to the fore. With the effective visuals we use, we can easily convey the message we want to give to the audience we present. Because people can better understand and analyze something they see visually.
So why do we need to visualize the data we have? Because the amount of information we gain through visual means is much higher than other sense organs. With the help of visualization, we can deal with complex data and perceive the whole process more easily. It is of great importance to be able to visually express the information that emerges as a result of studies to be carried out in the field of data science and reports to be made using any data source.
Of course, the processes such as data modeling, data cleaning, data manipulation, data analysis, which we do before visualization, are the most important parts of the work. At the conclusion, we have reached, if we cannot present them to the end-user in an interesting and exploratory way, we may have wasted the whole process.
Key Points in Data Visualization
The important points I observe when visualizing data are:
- The color palette to be used,
- The colors of the report are appropriate with the corporate colors,
- Legibility of texts on colors,
- The harmony between graphic colors and text colors,
- Choosing a visual graphic suitable for the data,
- Presenting the flow of visuals in a not boring way.
In this way, we can list these items. If I interpret them, for example; Imagine you’re doing data visualization in a corporate company. While corporate colors are navy blue and white, it is not pleasant to the eye not to include these tones in the reports or to create a report consisting of colors that are opposite to dark blue and white. Or how interesting can a visuality in which the colors you use in the whole of the report are incompatible with each other be? Other than that, how understandable would it be to visualize data that you can show in time breakdown, for example, on a pie chart? Or what would it be like to write the text in a dark text box in black? These are some of the things that should never be done through experience in data visualization.
Finding the Story of Data Set
When we are going to visualize the data we have, it may not be useful to proceed unplanned. Because for data that has a certain meaning, it may not make sense to show the visuals of this data with random graphics. For example, let’s say we have sales data that express trends. It may make sense to use a line chart or scatter chart to illustrate this trend in the most meaningful and eye-catching way. When we use the bar graph to show the same trend, people reading the report on the opposite side may have trouble grasping and understanding the report quickly. Of course, we need to get to know the audience on the side where we will present the report.
The importance of finding the story of the dataset stands out here. It is necessary to first examine this data and find out what relational data groups mean when they are combined. In short, it is necessary to know the data. But let’s say that we have made a visualization without understanding and examining the story of the data we have, can’t we do? Of course, we can do it. However, we may lose our way because we will intervene in the data in an unplanned way in our visualization. Therefore, it is important to never skip this step when visualizing data.
Why Should We Create a Color Palette?
If you are new to data visualization, creating a color palette may be a detail you don’t care about. Because the first purpose for beginners is to learn the data visualization (Business Intelligence) program comprehensively and to reach the level where they can make applications. However, we need to attach great importance to the colors and design we will use to keep the reproducibility of the report at a high level as well as using the program. If you ask why I insist on the color palette, it is all about maintaining the integrity of the report. Because if we use random colors that are not in harmony with each other, we will get colors that will grin on the report and an unpleasant appearance. This will eventually require us to rework the report.
There are many color palette creation sites where you can get help on which colors to reference while creating the colors to use. These sites give you HTML or hex codes of colors by creating color palettes that you can use in different formats. Thus, you can quickly create the palette in the reporting program you have used and use it practically.
Additional Information for Data Visualization
You must have researched the icon form of a logo or a shape in png format before. I am talking about images and icons that do not have a white background. If you are doing data visualization, you must have icon sets that you can use in the data you visualize. For example, you can use these icons to display KPIs and create a nice look. (KPI: Key Performance Indicator)
When you visualize the data by paying attention to such tricks, you can make very interesting, highly readable reports. Also, it is very easy to give the message you want to highlight to the user clearly when you pay attention to the necessary details. If you only know what you’re doing and what story you’re visualizing, you can create reports with great visuals.
