In the introductory study of data visualization, we should be alert to pitfalls and misunderstandings and grasp key nodes

With information technology 、 The popularization and application of new generation technologies such as digitalization , Data quickly became popular in society , And because of the scale effect and its own data value , Became the successor land 、 Labour 、 capital 、 The fifth largest factor of production after Technology .

Data has become the consensus of social development , Enterprises want to have an advantage in the future competition , Access to the growing digital economy , Data must be regarded as the strategic resource of the enterprise , Use data visualization to transform data into information , Promote enterprise development .

What is data visualization

The concept of data visualization is actually very simple , Because data visualization is a compound word , It is a combination of data and Visualization , The name explains the concept of data visualization . say concretely , Data visualization is based on graphical means , The massive amount of data that cannot be processed by human beings are expressed in visual charts , Convey information clearly and effectively .

Data visualization - Parker data business intelligence BI Visual analysis platform

Data visualization is an extension of data analysis , Analysts use statistical analysis methods , Convert data into information , Then carry out visual display . So with the deepening of digitalization , The amount of enterprise data is growing rapidly , The importance of data is also increasing , Data analysis 、 The demand for data processing such as data mining is increasing , Data visualization has officially become the favorite of enterprises .

The key to data visualization

Data visualization is a technical means that integrates data analysis and visual presentation , Its breadth and depth have been further strengthened on the basis of both , Only by mastering the key to data visualization , Understand the stages that need attention , Introductory learning will grow rapidly .

1、 Readability

Although there is a high threshold for data visualization , It needs to be designed and produced by professional data visualization personnel , However, the visual report and data visual analysis report are provided to business and management personnel , Therefore, it is necessary to optimize the readability in the production process . Only the readability optimization has been completed , Let the demander see the visual report , That's what makes sense . Otherwise , The visual analysis of these data can only be self admiration , Can not provide real value to the enterprise .

2、 Logicality

Data visualization is an extension of data analysis , What analysis needs most is logic . The data visualizer receives the analysis task , In confirming requirements, we need to rely on logic , Summarize business requirements , Confirm business indicators , Summarize and analyze the topic, etc ; In the analysis , Need logic , Mining the relationship between the data of each department , Find out how the trend changes , Judge and forecast business development, etc ; In visual presentation , It needs to be made by logic with data “ A novel ”, Through the theme 、 Thread 、 scene 、 Dialogue to show the value information behind the data , Assist managers in making decisions .

Data visualization screen - Parker data business intelligence BI Visual analysis platform

3、 accuracy

Data visualization can also be called art design to some extent , There are even many enterprises that emphasize the attribute of beauty when recruiting , This point is emphasized mainly for the readability mentioned above , Or external display properties . However, when data visualization personnel conduct data visualization analysis , Remember that accuracy should be a top priority , Starting from business needs , Make visual reports based on what is analyzed , Not for lines 、 Chart 、 Layout, etc , Adjust the data , In order to conform to aesthetic design .

4、 Uniformity

Try to keep one theme on the same page of data visualization , Make every chart included relevant to the topic 、 The data information presented is also consistent with the theme , At the same time, the color matching in the page 、 Layout 、 The style should be as consistent as possible . Every chart in the data visualization page space should be meaningful , You can't make a hammer , West a mallet , This causes production analysis to appear in the sales analysis report , Let the business and management look at it and lose the theme , Only if the chart module can clearly express the information that the analyst wants to convey , Enterprises and individuals can obtain information increment .

The trap of data visualization

actually , The key of data visualization can also be regarded as the trap of data visualization , The two are of equal importance , However, in order to avoid making mistakes in data visualization , It is more specific for some , Also frequently encountered problems are explained again .

Data visualization - Parker data business intelligence BI Visual analysis platform

1、 Data visualization is too gorgeous

Although beauty is a complicated word , There are also differences in different styles , But in practical application , Many new people see beauty , In my heart and gorgeous 、 Complexity is hooked , This is a trap that many data analysts are likely to encounter . Data visualization should be concise 、 Intuition is the first element of design , Ensure that the data can be clearly presented to users , Instead of hiding key information with gorgeous graphics , Let users find data by themselves , Leading to the opposite , Make data visualization a face project .

2、 Too much note text

Data visualization requires annotation text , Assist business and management personnel to understand , Guide the viewer to follow the main line , But everything is too much , This is especially true of annotation text . Data visualization is popular in enterprises because charts can clearly convey information , If analysts believe that graphical means cannot convey a complex amount of information , And add a large number of notes to the visual report , It's back to the period of data analysis report , It makes visualization meaningless .

Data visualization screen - Parker data business intelligence BI Visual analysis platform

3、 There is no plan for page layout

Data visualization can be so popular , There is a very important reason , That is, data visualization can be done in PC、 Move 、 Large screen and other terminals , Able to adapt to various scenarios . But switching between different scenes , It also increases the difficulty of data visualization design and production , After all, different terminals have different sizes of interfaces , There are also corresponding usage scenarios . Subject to page size restrictions , Or the vertical screen interface of the mobile terminal , There's a different logic , The amount of data and information presented is also very limited , In this case, the analyst should classify the data and information , Highlight the core data , Instead of arranging all the data on the page , There is no relevance , Difficult to obtain information .