I believe that many data people will be troubled by a question is, as a data analyst, why I do dynamic data visualization is time-consuming and laborious and does not look good, while others do THE GIF is easy and elegant?
Here, the editor shares several elements of a good dynamic data visualization:
1. Clear theme
In fact, before we do many things, we also need to determine a theme for this item in advance, and the production of the GIF is the same. Around this theme, we identify the important factors under this theme one by one, and some irrelevant charts can be appropriately discarded.
2. Logic
An excellent dynamic data visualization chart must have clear priorities. The size, layout and text of its GIFs are arranged and combined according to this. Related giFs should be put together and read in a certain order, so that users can easily understand them.
3. Readability
Data visualization is the purpose of the complex data simplification, enables users to quickly obtain the useful information being presented, don’t cram too much useless in dynamic graph elements, and the role of main characters is a supplementary description, to as far as possible concise and accurate description, in addition, also should maintain the consistency of the name, time, number, unit.
4, aesthetic
If you want users to be more patient with visual reports, you need to pay attention to the aesthetics of the reports. The first step to aesthetics is to harmonize, including the alignment of all components on the interface, as well as the color scheme. The second step is to make good use of color. Of course, we are not designers, and it is normal that we do not know about color matching. At this time, we can go to professional color matching websites to find color matching schemes.
5. Make your chart work
To put it simply, dynamic data visualization is to enable users to achieve exploratory analysis according to their own needs through dynamic effects and interaction between various elements.
The last point is the focus of this article. So, how do we make this graph work?
There are four basic steps:
1. Data analysis
It is necessary to make clear which data needs to be selected for dynamic data analysis, analyze the types of each data and the association between each data, discard some irrelevant data elements, and finally reserve the available data.
2. Determine the chart type
We have known of the chart types is the line chart, a pie chart, histogram and so on, may be making a dynamic data visualization in multiple data needs corresponding chart types, but in production, will need to pay attention to also do not require all data into one picture, the right data to select the right diagram type, and make the data more intuitive is the destination.
3. Select a template
Different themes need to match different styles. After the initial prototype of the dynamic data visualization chart, people need to decide on the style of the chart, such as what color scheme they are; Whether to make real-time dynamic data visualization chart; Which piece to add favorite special effects and so on.
4. Continuous optimization
The making of a GIF is a process of continuous optimization. As a graphic producer, he may not be able to see any defects in his own GIF, so he needs other people’s opinions to beautify the graph, and the final result is that both sides are satisfied.
It is not easy to complete the dynamic data visualization chart. Apart from the data information of time series analysis, there are also dynamic relative path data information and real-time motion trajectory data information, which must use special tools for dynamic.
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Let’s take a look at the GIF template created with this tool:
Data real-time refresh problem, in fact, now many products have been able to meet the requirements, Smartbi data visualization tool is one of them.
Not only can you refresh data in real time, but you can also customize the refresh interval. It is small to fill in reports, query, deployment, integration, visualization to the large screen, dashboard cockpit, everything, very powerful. Most importantly, because of this tool, the data architecture of the entire company can be standardized, and the next step is to build the big data platform of the enterprise. And IT is written in Java, support secondary development, Excel class designer, whether IT or business, getting started are very simple: edit SQL optimization, data set reuse is simply a small case, greatly reducing the threshold of report development.