Intelligent Data Insight
Intelligent Data Insight
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Intelligent Data InsightDataWind User GuideVisualized Query and AnalysisChart IntroductionChart Overview
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Download PDFCopy pageDownload PDFData analysis dashboards are presented using charts as carriers. Selecting the right chart enables faster and more accurate communication of information to readers. However, BI products offer a wide variety of chart types, each suited to different scenarios. How should we choose charts to display our data?
Typically, based on the structure of the data to be displayed, charts can be divided into four main types: comparison, relationship, composition, and distribution/geography. On this basis, consider data variables to determine which chart type is more appropriate.
Chart name | Application scenario | Common application examples |
|---|---|---|
Tables display statistical or detailed data, or data changes. | View sales amount, cost, and profit for each region, channel, and primary category, requiring clear and detailed data presentation or viewing data changes. | |
Display metric values for different categories. | View sales amount by category, sorted from highest to lowest. | |
Display metric trends over time. | View monthly income trends, sorted chronologically. | |
Display metric values for different categories as they change over time. | View monthly sales amount by channel. | |
Use different axis chart types and Y-axis ranges to display two sets of metrics with large differences in value ranges. | View daily income, and display month-over-month changes on the secondary axis. | |
Display the proportion of different categories | View the proportion of total sales revenue by channel | |
Display geographic information data by province/country | Use color to view the distribution of sales revenue across provinces | |
Compare two metrics under the same dimension | View sales revenue and sales volume by channel | |
Display charts of the same dimension together | View combined sales revenue, cost, and profit by channel | |
Display the relationship between two continuous data points, usually showing the impact of one metric on another | View the relationship between sales revenue and selling price | |
Display large amounts of text data, typically used to describe keywords or tags | View the video tag word cloud, measure weight by the number of videos, and highlight tags with more videos in the center | |
Display data distribution and frequency across different intervals | View the selling price distribution of product A from manufacturer A over the past year | |
Intuitively display metric values, usually core metrics | View total DAU | |
Display data funnel | View the conversion funnel for homepage visitors, video viewers, and likes, including user counts and conversion rates | |
Display multidimensional evaluation scores | View the category interest distribution of users who purchased product A | |
Display traffic distribution or data flow under different dimensions | View the distribution of new users by channel, campaign, and region | |
Display the completion rate of metrics | Monitor the progress of KPI completion | |
Express the quantitative change relationships among several specific values | Display the structure or sequence changes of the total score | |
Sparklines in individual table cells | View changes in profit in the raw-data table | |
Display the completion status of objectives | View the completion rate of monthly, quarterly, and annual targets for business metrics, the progress within the current cycle, and the year-over-year and period-over-period comparisons for each metric. |
(1) When there are too many legend data points to render a chart, it will automatically switch to a table.
(2) Table, column chart, bar chart, line chart, and area chart support custom field capabilities. At the bottom of the chart configuration area, you can enable "Custom field". Note: Only metric fields are supported.
