Data Visualization

Stacked Column Chart

A stacked column chart is useful when you want to analyze the contribution of one to the whole. This type of comparative bar chart is preferred when the number of series exceeds two (multiple series). Using only one data series in the stacked column chart looks similar to the normal column chart. Typically, it illustrates vertically how a bigger data series comprises smaller series. This type of visualization is easy to compare several data series, but the complexity and readability increase proportionately. Here, the X-axis represents the different product categories (dimensions), and the Y-axis represents its measures (metrics) of the different costs involved in a Cost of Goods Sold stacked one over the other.

Functionality/ Features:

In the stacked column chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

2. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

3. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

100% Stacked Column Chart

A 100% stacked column chart demonstrates the part-to-whole proportions over time/ category. It vertically displays the multiple data series in stacked columns (one over the other) of equal height with the relative percentage of the smaller series where the total of each column is always equal to 100 %. It works better when you need to view the relative proportions of various products to their total measurement unit. This chart differs from a stacked column chart by displaying the percentage value, not the absolute value. It is limited to analyzing percentage-based interpretation among the data sets. Typically, the X-axis represents the break-ups in dimensions, and the Y-axis represents the relative proportions of various products to their total value.

Functionality/ Features:

In the 100% stacked column chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

2. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

4. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

Bar Chart

A bar chart presents the summarized form of categorical data. It compares multiple categories in rectangular bars in which the height of the bar is proportional to the sum of the values it represents. Compared with a column chart, a bar chart differs in orientation and displays the dimensions (multiple categories) on the Y-axis and metrics (measured values) on the X-axis. (i.e) Both the axes are interchanged when you compare them with the column chart. Moreover, in a Single dimensional bar chart, we can use up to five metrics, and in a two-dimensional bar chart, we can use ‘n’ number of data series with the limitation of only one metric.

Functionality/ Features:

In the bar chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

2. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

3. Breakdown dimension

   This option allows you to see the analysis for multiple dimensions at the same time in the same chart.

4. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

5. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

Stacked Bar Chart

The stacked bar chart is the horizontal version of the stacked column chart. It helps us to compare multiple data sets simultaneously. We can map the data from left to right using horizontal rectangular bars. It displays the components and its sub-components by stacking one over the other in a compact space. Depending on the visual comfortability, stacked column charts and stacked bar charts can be interchanged.

Functionality/ Features:

In the stacked bar chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

2. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

4. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

100 % Stacked Bar Chart

A 100% stacked bar chart is the horizontal version 100% stacked column chart. This chart type analyses the part-to-whole proportions of multiple data sets over time/ category. It horizontally displays the multiple data series in stacked bars (one over the other) of equal height with the relative percentage of the smaller series where the total of each bar is always equal to 100 %. Compared with a stacked bar chart, it will map the information about the parts of some whole and not the whole and how they vary. This kind of visualization is strictly limited to certain cases. Typically, the Y-axis represents the break-ups in dimensions, and the X-axis represents the relative proportions of various products to their total value.

Functionality/ Features:

In the 100% stacked bar chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

2. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

4. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

Table

A Table chart is another type of chart to analyze the data visually. Tables organize the information by grouping the data in a grid of rows and columns. Rows represent the data records, and columns represent the dimensions or metrics. The metric aggregations in the table are based on the aggregation type (median, sum, average, count, count distinct, min, max, median, standard deviation, and variance) for that metric. In Tables, mapping multiple dimensions and metrics to identify the patterns and relationships is possible. Therefore, tables are handy when we are in a situation to compare multiple dimensions and metrics without complex visualization techniques.

Functionality/ Features:

In the table chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

2. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

4. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

5. Conditional formatting

   Conditional formatting modifies the appearance of a cell range based on a condition (or criteria). It highlights the cells that contain values which meet the given condition.

6. Summary row

   The summary row option displays the automatic sum or average of the columns in a table. It is easy to use this function by simply marking the “Summary Rows” option in the Table Properties.

Table with Bar Chart

A table with bar chart is a combination of table and bar to mention the metrics inside the table chart by visuals (bars) with/ without numbers. Instead of searching the numbers in the chart, this type of chart helps the audience to grasp the priorities like maximum, minimum, which one is first, second or any quickly. This is highly preferred when you want to display the values with ranking comparisons.

Functionality/ Features:

In the table with bar chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

2. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

4. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

5. Conditional formatting

   Conditional formatting modifies the appearance of a cell range based on a condition (or criteria). It highlights the cells that contain values which meet the given condition.

6. Summary row

   The summary row option displays the automatic sum or average of the columns in a table. It is easy to use this function by simply marking the “Summary Rows” option in the Table Properties.

Table with Heatmap

A Table with Heatmap is almost similar to a table with bar chart. It uses colours instead of having bars with different heights to highlight the metrics. For example, displaying the highest value (most priority) with dark green and subsequent data (least priority) with step-by-step hue/ intensity shifting based on the importance. This chart helps us understand the information without looking into too many numbers.

Functionality/ Features:

In the table with heatmap chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

2. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

4. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

5. Conditional formatting

   Conditional formatting modifies the appearance of a cell range based on a condition (or criteria). It highlights the cells that contain values which meet the given condition.

6. Summary row

   The summary row option displays the automatic sum or average of the columns in a table. It is easy to use this function by simply marking the “Summary Rows” option in the Table Properties.

Scorecard

Scorecards are used to show the key performance indicators (KPIs) and to evaluate a single metric value over a particular baseline value. It uses numbers and optionally names to highlight the KPIs. Scorecard has only metrics and does not have dimensions. It can compare the results against your strategic goals. This type of visualization is preferred when we want to measure your organization’s progress in terms of revenue, average sales, the number of products passed the QC, etc.

Functionality/ Features:

In the scorecard chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Conditional formatting

   Conditional formatting modifies the appearance of a cell range based on a condition (or criteria). It highlights the cells that contain values which meet the given condition.

2. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

Scorecard with Compact Number

A scorecard with compact number is the same as a scorecard, but the metric figures are rounded off. In addition, it displays the unit indicators in a way that how the metric is configured in the data source. For example, Consider the value: 694,847; the Scorecard chart displays the value as 694,847, but the Scorecard with compact number displays the value as 694.8K. This chart type is preferred when all the significant figures after the decimal point are not important to highlight the KPIs.

Functionality/ Features:

In the scorecard with compact number chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Conditional formatting

   Conditional formatting modifies the appearance of a cell range based on a condition (or criteria). It highlights the cells that contain values which meet the given condition.

2. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

Pie Chart

A pie chart is a circular 360-degree chart that splits the total value/ percentage into radial slices of different angles and arc lengths. The size of each pie segment corresponds to the quantity it contributes. It works best when we compare a statistical data set with a few variables and large variations. Like bar charts, Pie charts can also analyze both qualitative and quantitative data. One dimension and one metric are needed to plot it. A pie chart represents the value, not the time, so it is preferred when the analysis does not require changes in metrics over time.

Functionality/ Features:

In the pie chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

2. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

4. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

Doughnut Chart

A doughnut chart is a kind of Pie chart to analyze the contribution of the parts to its whole with the centre space/ hole using the arc length. Unlike Pie, we can add extra information in the centre space. Compared to Pie, a doughnut chart can analyze more than one data series with inner and outer circles. The doughnut chart type is preferred when your data series does not have zero or negative values and visually works well for data series with few categories.

Functionality/ Features:

In the doughnut chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

2. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

4. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

Line Chart

A line chart is a type of visualization technique in which the metrics are represented in dots/ points, and the dots/ points are connected via a line horizontally. It expresses the correlation between the values over time and may have single or multiple lines based on the data series. Like Bar and column charts, X-axis and Y-axis compare the dimensions and metrics. However, line charts are continuous over time compared to bar and column charts. Moreover, in a Single dimensional line chart, we can use up to five metrics, and in a two-dimensional line chart, we can use ‘n’ number of data series with the limitation of only one metric.

Functionality/ Features:

In the line chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

2. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

4. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

5. Breakdown dimension

   This option allows you to see the analysis for multiple dimensions at the same time in the same chart.

Smoothed Line Chart

A smoothed line chart is an extra option in the line chart that smoothens the corners to display eye-friendly visualization. This chart type is preferred over a normal line chart when you use larger data sets. It expresses the potential relationships and in-depth fluctuations between the values over time.

Functionality/ Features:

In the smoothed line chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

2. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

4. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

5. Breakdown dimension

   This option allows you to see the analysis for multiple dimensions at the same time in the same chart.

Combo Chart

A combo chart combines two charts, typically a line chart and a column chart. This chart type is preferred to analyze multiple data series and to compare them using different scales with the limitation of only one dimension. In addition, it is useful when we compare wider ranges of a data set and two different data sets simultaneously.

Functionality/ Features:

In the combo chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

2. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

4. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

Stacked Combo Chart

A stacked combo chart combines two charts, typically a line chart and a column chart, with multiple data sets stacked one over the other. It works better if we display the contribution of each data point to the total in a category. This chart type is preferred when we want to analyze two or more similar metrics over a line. It is further divided into single and dual-axis charts. Compared to a normal combo chart, a stacked combo chart displays two or more metrics in the same column, thus reducing the readability to a certain extent.

Functionality/ Features:

In the stacked combo chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

2. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

4. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

5. Breakdown dimension

   This option allows you to see the analysis for multiple dimensions at the same time in the same chart.

Time Series Chart

A time series chart plots the series of data points between the horizontal X-axis as the time dimension and the vertical Y-axis as metrics. It illustrates the changes in measured values(metrics) over time. Timeseries and Line charts are almost similar, but X-axis in the time series chart is always time-based. Like bar and line charts, we can use up to five metrics in a Single dimensional time series chart, and we can use only one metric in a two-dimensional time series chart. It is preferred when we need to analyze the daily/ regular people movement, profits or sales numbers etc., over time.

Functionality/ Features:

In the timeseries chart, the users will be able to leverage the following features/ functionality based on their needs.

1. The dimension of this chart type must be a date.
2. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

3. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

4. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

5. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

Smoothed Time series Chart

A smoothed time series chart is a special category under a time series chart to identify the trends and patterns clearly by removing the irregular roughness in the graph. It expresses the potential relationships and in-depth fluctuations between the values over time. Smoothing is preferred when the data sets have fewer deviations over time. It is further classified into motion average and exponential smoothing.

Functionality/ Features:

In the smoothed timeseries chart, the users will be able to leverage the following features/ functionality based on their needs.

1. The dimension of this chart type must be a date.
2. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

3. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

4. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

5. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

Area Chart

An area chart is the advancement of Line/ Time series charts that display the variations in the quantities/ metrics on a two-dimensional cartesian system over time. The portion below the lines is shaded or coloured compared to line charts. We shall use different colours to highlight the layers in the area graph. This chart type is easy to interpret, but we cannot find the exact values. It is preferred when data total is important and works better when we have one dimension and one metric without large variations.

Functionality/ Features:

In the area chart, the users will be able to leverage the following features/ functionality based on their needs.

1. The dimension of this chart type must be a date.
2. Breakdown dimension

   This option allows you to see the analysis for multiple dimensions at the same time in the same chart.

3. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

4. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

5. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

6. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

Stacked Area Chart

A stacked area chart plots multiple data series over a baseline by stacking one over the other. It is used to analyze the relative proportions and part-to-whole comparisons or cumulative values in multiple data series. This chart is not suitable for plotting negative values. Compared to other line charts, readability is less. However, visualizing the contribution of one value to its total helps us understand the priorities.

Functionality/ Features:

In the stacked area chart, the users will be able to leverage the following features/ functionality based on their needs.

1. The dimension of this chart type must be a date.
2. Breakdown dimension

   This option allows you to see the analysis for multiple dimensions at the same time in the same chart.

3. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

4. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

5. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

6. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

100% Stacked Area Chart

A 100 % stacked area chart shows the relative percentage of the individual to total contributions over a common baseline by stacking the multiple quantities on top of others. It expresses the progression and composition percentage over time and helps us to identify the KPIs. Like stacked area charts, readability decreases with the increase in data series. Typically, the X-axis represents the break-ups in dimensions, and the Y-axis represents the relative proportions of various products to their total value.

Functionality/ Features:

In the 100% stacked area chart, the users will be able to leverage the following features/ functionality based on their needs.

1. The dimension of this chart type must be a date.
2. Breakdown dimension

   This option allows you to see the analysis for multiple dimensions at the same time in the same chart.

3. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

4. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

5. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

6. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

Scatter Chart

A scatter chart displays the correlation between the two continuous variables using dots. This chart type can identify the trends by predicting the oddities in the data more effectively while using larger data sets. At the same time, it will not work for data sets with fewer data points. We can superimpose a trendline on the chart to show the data's overall direction. Data studio supports linear, exponential, and polynomial trendlines. It is preferred to find the correlation type (positive or negative) when the ranges of the two variables are close and suggested to avoid when the data ranges are irrelevant. It works best when we use colours and avoid overplotting.

Functionality/ Features:

In the scatter chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

2. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

3. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

Bubble Chart

A bubble chart is a kind of scatter chart which requires a minimum of three measured variables to compare and identify the relationship between them. The data point denotes the values of the first two variables like a scatter chart, and the bubble size shows the value of the third variable. Like a scatter chart, we can use colours for highlighting and labels for mentioning the specific texts. It is preferred to analyze the financial data like investment, value, and risk in a 3-dimensional plot.

Functionality/ Features:

In the bubble chart, the users will be able to leverage the following features/ functionality based on their needs.

1. The bubble size metric of this chart type is a compulsory field.
2. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

3. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

4. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

Pivot Table

A pivot table is a well-formatted, user-friendly chart to analyze and summarize large quantities of data that can be viewed from different perspectives to derive meaningful conclusions. Pivot tables compare the relationship between the data points via customized rows, columns, filters, and values. Pivot tables can handle up to 50,000 rows of data, 10 metrics, 5 dimensions for fixed-schema data sources and 10 dimensions for flexible-schema data sources. It is preferred to derive conclusions through statistical calculations. The Pivot table supports features like Expand-collapse, total-subtotal, colour highlighting, and headers.

Functionality/ Features:

In the pivot table chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Conditional formatting

   Conditional formatting modifies the appearance of a cell range based on a condition (or criteria). It highlights the cells that contain values which meet the given condition.

2. Expand-Collapse

   Expand-collapse lets report viewers show or hide different levels of information in the pivot table by clicking + and – in the column header.

3. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

4. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

Pivot Table with Bar

A pivot table with bar is a type of conditional formatting under a pivot table that expresses the value of the metrics using horizontal bars. It eases the visual comfort of analyzing and recognizing the values via coloured bars rather than searching the numbers. This chart type helps the key leaders to find the priorities like maximum, minimum, which one is first, second or any quickly after statistical calculations.

Functionality/ Features:

In the pivot table with bar chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Conditional formatting

   Conditional formatting modifies the appearance of a cell range based on a condition (or criteria). It highlights the cells that contain values which meet the given condition.

2. Expand-Collapse

   Expand-collapse lets report viewers show or hide different levels of information in the pivot table by clicking + and – in the column header.

3. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

4. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

Pivot Table with Heatmap

A pivot table with heatmap is a type of conditional formatting under a pivot table that expresses the value of the metrics using coloured background with different intensities varying between low, medium, and high. This chart type uses the contrast levels to compare and recognize the key metrics or KPIs which will increase the decision-making. Readability is comparatively more elevated in the pivot table with bar and heatmap than in the normal pivot table. Therefore, based on the visual comfort and interpretation, we can switch between the pivot table with bar and the pivot table with heatmap.

Functionality/ Features:

In the pivot table with heatmap chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Conditional formatting

   Conditional formatting modifies the appearance of a cell range based on a condition (or criteria). It highlights the cells that contain values which meet the given condition.

2. Expand-Collapse

   Expand-collapse lets report viewers show or hide different levels of information in the pivot table by clicking + and – in the column header.

3. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

4. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

Treemap

A tree map is an area-based visualization technique that portrays the complex data grouped and mapped based on the dimension hierarchies. It is preferred to analyze the relative significance and relationship between the different entities using branches or nodes represented in coloured rectangles. Larger rectangular boxes are used to mention the major branch, and smaller rectangles are used to mention the sub-categories. This chart type can drill down and display the category, subtotal, and hierarchies. The treemap supports features like drill-down, levels to show, colour highlighting, filters and headers. Precise comparison of larger data decreases with an increase in colours and multiple branches.

Functionality/ Features:

In the treemap chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

2. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

4. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.

Gauge Chart

A gauge chart is like a bullet chart that displays the single and most important insight (metric) against target benchmarks using dial like speedometers. It optionally supports additional metrics by selecting from drop-down options. The needle/centre bar in the dial indicates the key business metrics against the target value. The metrics can be plotted as compact numbers or with decimal precision. Compared to bullet charts, gauge charts are easy to interpret but difficult to find the values as they measure the angle, not distance. The gauge chart supports features like colour highlighting, filters, headers, and metric comparisons. However, this chart type is rarely preferred as it lacks context and contains too little information.

Functionality/ Features:

In the gauge chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

2. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

Gauge with Ranges

A gauge chart with ranges is the advancement of a gauge chart that displays the single and most important insight (metric) against target benchmarks using dial like speedometers. This chart type optionally supports more than one metric and consists of four components; The centre bar represents the actual measured value, the optional vertical line represents the target value, coloured bands represent the threshold ranges, and optionally, it has a comparison value. Compared to bullet charts, it supports up to five ranges viz poor, average, good, very good and excellent. In comparison with normal gauge charts, it can map minimum, maximum, target and comparison values with ranges.

Functionality/ Features:

In the gauge with ranges chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

2. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

Bullet Chart

A bullet chart displays the single and most important metric against target benchmarks up to three ranges poor, average, and good. This chart type optionally supports more than one metric and consists of three components; The centre bar represents the actual measured value, the vertical line represents the target value, and the coloured bands represent the threshold ranges. In addition, the bullet chart supports features like drill-down, colour highlighting, headers and filters. This chart type is preferred when we need to display the progression of key metrics and compare the same with the projected values to understand the situation better.

Functionality/ Features:

In the bullet chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

2. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

Bubble Map

A bubble map is a type of google map that increases the functionality by displaying the data source with valid geo fields. This chart type plots the data points in the form of coloured circles and supports two parameters in which one is represented by bubble size and the other is represented by bubble colour. It helps us to analyze up to 1 million bubbles for longitude and latitude fields and up to 3500 bubbles for other geographic field types. Compared to the geo chart, this chart type supports satellite view and does not support the features drill-down and optional metrics. However, here we can zoom in on a particular area and click the bubbles for detailed information.

Functionality/ Features:

In the bubble map, the users will be able to leverage the following features/ functionality based on their needs.

1. This chart type supports the users to see a Map view as well as a Satellite view.
2. Geographic Location is a mandatory field in this chart.
3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

Filled Map

A filled map is another type of google map that increases the functionality by displaying the data source with valid geo fields. This chart type plots the data in the form of shaded areas over geographic dimensions like ZIP code, country, and state. Unlike a bubble map, this will not support the latitude, longitude, and types of geographic fields. Like bubble map, filled maps require one or more dimension in the data source we need to plot, supports satellite view, and does not support the features drill-down and optional metrics. A postal code can be an international or U.S ZIP code in bubble charts, whereas it shall be a U.S zip code in filled maps.

Functionality/ Features:

In the filled map, the users will be able to leverage the following features/ functionality based on their needs.

1. This chart type supports the users to see a Map view as well as a Satellite view.
2. Geographic Location is a mandatory field in this chart.
3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

Heat Map

A heat map is another type of google map that increases the functionality by displaying the data source with valid geo fields. This chart type plots the data using different colour gradients/ codes over geographic dimensions like ZIP code, country, and state. It works best when analyzing the volume of locations or events in a dataset. Like bubble and filled maps, heat maps require one or more dimension in the data source we need to plot, supports satellite view, and does not support the features drill-down and optional metrics.

Functionality/ Features:

In the heat map, the users will be able to leverage the following features/ functionality based on their needs.

1. This chart type supports the users to see a Map view as well as a Satellite view.
2. Geographic Location is a mandatory field in this chart.
3. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

Geo Chart

A geo chart is a map-type visual chart that analyzes and compares the location-based measurement values (metrics). To plot a geo chart, we require three components: a geographic dimension, a metric and the map’s zoom area. Here the dimension represents the country, city, region etc., metric represents the measured values we need to plot, and Zoom area defines the area of the world map we need to display. A geo chart has the limitation of selecting the first 5000 data rows in descending order unless we mention the field type. This chart type is preferred to analyze a huge volume of data. For example, analyzing the number of units sold across the cities, countries, or continents helps us derive meaningful inferences, enabling us to understand the market and reach insights.

Functionality/ Features:

In the geo chart, the users will be able to leverage the following features/ functionality based on their needs.

1. Geographic Location is a mandatory field in this chart.
2. Drill down and Drill up

   This function allows you to go much deeper into more detailed data or information layers by drilling down (downward arrow) and vice versa by drilling up (upward arrow).

3. Optional metrics

   It allows you to see the analysis for multiple metrics at the same time in the same chart.

4. Calculated measures

   This feature allows you to use custom-created measures calculated with the help of already available measures in a dataset.

5. Metric Slider

   This feature helps you to set a metric range in which you want to see the analysis, which can be done by moving the slider.