What are the best chart types for visualizing time-series data in BI? (2024)

Line charts are one of the most popular and versatile chart types for time-series data. They show the change of a variable over time by connecting data points with a line. Line charts are easy to read, compare, and customize. You can use line charts to show trends, seasonality, correlation, or deviation over time. You can also use multiple lines to compare different variables or categories on the same chart. For example, you can use a line chart to show the monthly sales of different products or regions over a year.

Bar charts are another common and useful chart type for time-series data. They show the value of a variable over time by using horizontal or vertical bars. Bar charts are good for showing discrete or categorical data, such as counts, percentages, or rankings. You can use bar charts to show the distribution, frequency, or composition of time-series data. You can also use stacked or grouped bars to show the breakdown of a variable by another dimension. For example, you can use a bar chart to show the number of customers by age group over each quarter.

Area charts are similar to line charts, but they fill the area below the line with a color. Area charts are useful for showing the magnitude or proportion of time-series data. You can use area charts to show the cumulative or relative change of a variable over time. You can also use stacked or layered area charts to show the contribution of different variables or categories to a total. For example, you can use an area chart to show the total revenue and the revenue by product category over a year.

Candlestick charts are a special type of chart that shows the high, low, open, and close values of a variable over time. Candlestick charts are often used for financial or stock market data, as they can show the volatility and direction of price movements. Each candlestick represents a time period, such as a day, a week, or a month. The body of the candlestick shows the difference between the open and close values, and the color indicates whether the value increased or decreased. The wicks of the candlestick show the range between the high and low values. You can use candlestick charts to show the trends, patterns, and signals of time-series data.

Scatter plots are a type of chart that shows the relationship between two variables over time by using dots or markers. Scatter plots are good for showing the correlation, distribution, or outliers of time-series data. You can use scatter plots to show how one variable affects another variable over time, or to identify clusters or gaps in time-series data. You can also use different colors, shapes, or sizes to show additional dimensions of time-series data. For example, you can use a scatter plot to show the relationship between sales and profit over time, and use colors to show the product category.

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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