Data Visualization Techniques
The growing amount of data and its importance to business makes data visualization an essential part of business strategy for many companies. In this article, we provide an in-depth review of data visualization techniques and tools, factors affecting the choice of visualizations, and the most widely used data visualization tools used in business today.
What determines data visualization Techniques
Visualization is the first step to realizing data. Data analysts use a wide range of techniques to translate data and data interactions in a simple way – maps, charts, graphs, etc. Choosing the right technique and its structure is often the only way to understand data. Conversely, poorly selected tactics will not allow you to open the full potential of the data or make it inappropriate.
5 factors that influence data visualization Techniques
- Audience: It is important to adjust the data representation for the specific target audience. For example, Exercise Mobile App users can easily work with seamless visualizations while browsing their progress. On the other hand, if you intend to continue working with data for data intelligence researchers and experienced decision makers, you can often go beyond simple diagrams.
- Content: The type of data you handle will determine the tricks. For example, if it is a time-series measurement, in many cases you will use line charts to show the dynamics. Scatter layers are often used to show the relationship between two components. However, bar charts plan for comparative needs.
- Context: You can use different data visualization approaches and read the data depending on the context. To emphasize a certain number, for example, significant profit growth, you can use shades of one color on the chart and highlight the highest value with brightness. Instead, you can use different colors to differentiate the elements.
- Dynamics: There are different types of data, and each type has a different rate. For example, financial results can be measured monthly or annually, while time series and tracking data are constantly changing. Depending on the rate of change, you may want to consider dynamic representation (steam) or standard visualization techniques in data mining.
- Purpose: The aim of data visualization also affects by implemented way. In order to perform a complex analysis, visualization is compiled into dynamic and controllable dashboards that act as visual data analysis tools and tools. However, dashboards are not required to display single or occasional data intelligence.
Data visualization techniques and tactics
Relying on these factors, you can choose various data visualization techniques and configure their features. Here are some common types of visualization choices:
Get to know the audience
The IT and Internet age as we know it seems to last forever, but let’s not forget that it is still in its 20s. On the other hand, data visualization is younger than that. A lot of people, moreover also entrepreneurs, don’t know how to check more than a simple chart or pie chart. That’s why you need to understand the target audience and modify the presentation to match their IT knowledge.
Think about the content
What you want to present is important to who you show it to. There are 4 basic ways to access data visualization:
- Scatter plot is the best choice in this case as it shows the interactions and interactions between specific components.
- The line graphics fit exactly if you want to show how a particular event develops over time.
Mind the colors
While this may seem inappropriate, the colors you choose will strongly affect the overall performance of your data visualization model. You need to keep 2 things in mind here: color consistency and contrast throughout the document.
First, you need to emphasize the differences between these features and make the contradictions between the opposite elements. Second, you should not mix colors too much because it creates confusion among the audience and interferes with already established patterns.
Use interactive maps
Data visualization becomes a source of valuable digital content that should include interactive elements in the presentation. Interactive maps play an important role in that category because they allow users to engage and view only the information they need. Creating such maps is a very complicated process, but it will definitely have a huge impact on your customers or clients.
Use digital tools
There are dozens of unbelievable data visualization tools available online. We strongly recommend that you use some of these programs to create custom tables, as this is the only way to impress your customers in 2018.
Conclusion
Data analysis helps to create better and more attractive business reports, increasing the efficiency of your analysis. If you need the attention of your clients and colleagues, you want to learn modern data visualization models to enhance the quality of your presentation.
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