Highlight data
If your dataset doesn't have many rows and columns, you can identify patterns and trends within the data. However, as the dataset grows, it becomes too large to do analysis without using another tools.
A visual indicator highlights data so you can quickly see patterns without having to dive deeply into it. An indicator is instantly readable and can show low or high values against a category, such as sales by region, without needing to read the numeric values within the column.
You can create a heat map by coloring a column based on value. A heat map uses an intensity color scale to represent the value within the column. The higher the value, the more intense the color, enabling you to quickly identify hotspots within your dataset. Heat maps work well with continuous values, and are an ideal solution if you have a temperature column.
You use data bars to compare the size of values in a column. The wider the bar, the higher the value in the column. This enables you to quickly discover the highest and lowest values.
You can also highlight data that falls within a set of criteria, such as values within a percentage range. By visually highlighting data, you instantly see the patterns of values within the dataset, which is necessary for quickly digesting the important business knowledge inside it.
In this video, you'll see how a heat map can be applied to a dataset to display the values within a column using a color scale: