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Area charts are a type of data visualization that display quantitative data over time or across categories. They are similar to line charts, but with the area beneath the line filled in with color or shading to create a solid shape.

Area charts are useful for showing trends in data, especially when comparing multiple data sets. They can also be used to emphasize the magnitude of changes in data over time or across categories. However, they can be less precise than other types of charts, especially when the data sets overlap.

When creating an area chart, it’s important to choose appropriate colors and shading to ensure that the chart is easy to read and interpret. It’s also important to label the axes clearly and provide a legend to help viewers understand the data being presented.

The main difference between area charts and line charts is that in area charts, the area beneath the line is filled in with color or shading to create a solid shape, while in line charts, only the line representing the data is displayed.

Here are some key differences between area charts and line charts:

1. Emphasis: Area charts place more emphasis on the magnitude of changes in data over time or across categories, while line charts focus more on the trends and patterns in the data.
2. Precision: Line charts tend to be more precise than area charts because they only display the line representing the data without the added shading or color that may obscure or overlap data points.
3. Data density: Line charts are better suited for displaying large data sets or data with many categories, while area charts may become difficult to interpret when multiple data sets overlap or when there are too many categories.
4. Interpretation: Line charts are easier to interpret for comparisons and relationships between multiple data sets, while area charts are better for showing how a single data set changes over time or across categories.

Ultimately, the choice between an area chart and a line chart depends on the specific data being presented and the intended message or insights to be conveyed.

Use-Cases for area-charts:

1. Stock Market Performance: An area chart can be used to show the performance of a stock market index, such as the S&P 500, over time. The chart would display the index value on the vertical axis and time on the horizontal axis. The area beneath the line would be filled in with color or shading to show the magnitude of changes in the index value.
2. Website Traffic: An area chart can be used to show the traffic to a website over time. The chart would display the number of page views on the vertical axis and time on the horizontal axis. The area beneath the line would be filled in with color or shading to show the level of traffic.
3. Sales by Product Category: An area chart can be used to show sales by product category over time. The chart would display the sales amount on the vertical axis and time on the horizontal axis. The area beneath each line, representing each product category, would be filled in with a different color or shading to differentiate between the categories.
4. Climate Data: An area chart can be used to show changes in climate data, such as temperature or precipitation, over time. The chart would display the data on the vertical axis and time on the horizontal axis. The area beneath the line would be filled in with color or shading to show the magnitude of changes in the data.
   
   

Create an Area Chart (microstrategy.com)

A heat map is a graphical representation of data in which different values are represented by different colors. In a BI dashboard, a heat map can be used to visualize patterns and trends in large datasets, making it easier for users to quickly identify areas of interest and focus their attention where it’s needed most.

Some use-cases for heat maps in BI dashboards include:

1. Sales Analysis: A heat map can be used to show the distribution of sales across different regions or territories. This can help sales teams identify areas where they need to focus their efforts in order to improve performance.
2. Customer Behavior Analysis: A heat map can be used to show the areas of a website or application where users are spending the most time. This can help designers and product managers identify areas of the user experience that need improvement.
3. Risk Management: A heat map can be used to visualize potential risks and their likelihood of occurrence. This can help organizations identify and prioritize risks in order to develop effective risk management strategies.

Some good practices for using heat maps in BI dashboards include:

1. Keep it Simple: Heat maps can quickly become overwhelming if there are too many data points or if the colors are too bright or contrasting. Stick to a simple color scheme and limit the number of data points in order to keep the visualization clear and easy to read.
2. Use Color Effectively: Choose colors that are easy to differentiate and that have meaning. For example, green might represent positive values, while red might represent negative values. Make sure that the color scheme is intuitive and easy to understand.
3. Provide Context: Heat maps are most useful when they are accompanied by other data or visualizations that provide context. For example, a heat map showing sales by region might be more useful if it’s also accompanied by a chart showing the overall sales trends over time.

Introduction to Heat Maps (microstrategy.com)