Dashboard visualization types
This article outlines the types of visualizations available to use in AI/BI dashboards and shows you how to create an example of each visualization type. For instructions on building a dashboard, see Create a dashboard.
Note
To optimize performance, charts can only render 10K rows or 10MB on the canvas, whichever is smaller. Otherwise, visualizations can be truncated.
Area visualization
Area visualizations combine the line and bar visualizations to show how one or more groups’ numeric values change over the progression of a second variable, typically that of time. They are often used to show sales funnel changes through time.
Configuration values: For this area visualization example, the following values were set:
Dataset: TPCH orders
Visualization: Area
Title:
Total price and order year by order priority and clerk
X-axis:
Field:
o_orderdate
Scale Type:
Temporal
Transform:
Yearly
Axis title:
Order year
Y-axis:
Field:
o_totalprice
Axis title:
Total price
Scale Type:
Quantitative
Transform:
Sum
Group by:
Field:
o_orderpriority
Legend title:
Order priority
Filter
Field:
TPCH orders.o_clerk
SQL query: For this area visualization, the following SQL query was used to generate the data set named TPCH orders
.
SELECT * FROM samples.tpch.orders
Bar chart
Bar charts represent the change in metrics over time or across categories and show proportionality, similar to a pie visualization.
Configuration values: For this bar visualization example, the following values were set:
Dataset: TPCH orders
Visualization: Bar
Title:
Total price and order month by order priority and clerk
X-axis:
Field:
o_orderdate
Transform:
Monthly
Scale Type:
Temporal
Axis title:
Order month
Y-axis:
Field:
o_totalprice
Scale Type:
Quantitative
Transform:
Sum
Axis title:
Total price
Group by:
Field:
o_orderpriority
Legend title:
Order priority
Filter
Field:
TPCH orders.o_clerk
SQL query: The following SQL query generated the data set TPCH orders
for this bar visualization.
SELECT * FROM samples.tpch.orders
Box chart
The box chart visualization shows the distribution summary of numerical data, optionally grouped by category. Using a box chart visualization, you can quickly compare the value ranges across categories and visualize the locality, spread, and skewness groups of the values through their quartiles. In each box, the darker line shows the interquartile range. For more information about interpreting box plot visualizations, see the Box chart article on Wikipedia.
Configuration values: For this box chart visualization, the following values were set:
X column (dataset column):
l-returnflag
Y columns (dataset column):
l_extendedprice
X axis name (override default value):
Return flag1
Y axis name (override default value):
Extended price
SQL query: For this box chart visualization, the following SQL query was used to generate the data set.
select * from samples.tpch.lineitem
Bubble chart
Bubble charts are scatter charts where the size of each point marker reflects a relevant metric. To make a bubble chart, select Scatter as your visualization type. In the Size setting, select the metric you want represented by the size of the markers.
Configuration values: For this bubble chart visualization example, the following values were set:
Dataset: NYC taxi trips
Visualization: Scatter
Title:
Trip distance, fares, and trip duration
X-axis:
Field:
trip_distance
Scale type:
Quantitative
Transform:
None
Y-axis:
Field:
fare_amount
Scale type:
Quantitative
Transform:
None
Color by:
Field:
pickup_zip
Size:
Field:
time_spent
Transform:
None
Combo chart
Combo charts combine line and bar charts to present the changes over time with proportionality.
Configuration values: For this combo chart visualization, the following values were set:
Dataset: partsupp
Visualization: Combo
X-axis:
ps_partkey
Scale Type:
Quantitative
Y-axis:
Bar:
ps_availqty
Aggregation type:
SUM
Line:
ps_supplycost
Aggregation type:
AVG
Color by Y-Series:
Sum of ps_availqty
Average ps_supplycost
SQL query: For this combo chart visualization, the following SQL query was used to generate the data set.
SELECT * FROM samples.tpch.partsupp
Dual-axis combo chart
You can use combo charts to show two different y-axes. With your combo chart widget selected, click the kebab menu on the Y axis settings in the chart configuration panel. Turn on the Enable dual axis option.
Configuration values: For this combo chart, the Enable dual axis option is on. The other configurations are set as follows:
Dataset: Trips
Visualization: Combo
X-axis:
tpep_pickup_datetime
Scale Type:
Temporal
Transform:
Weekly
Y-axis:
Left Y-axis (Bar):
trip_distance
Transform:
AVG
Right Y-axis (Line):
fare_amount
Transform:
AVG
Color by Y-series:
Average trip_distance
Average fare_amount
SQL query: The following SQL query was used to generate the data set:
SELECT * FROM samples.nyctaxi.trips
Counter visualization
Counters display a single value prominently, with an option to compare them against a target value. To use counters, specify which row of data to display on the counter visualization for the Value Column and Target Column.
You can set conditional formatting and customize the text style in the Value configuration details.
Configuration values: For this counter visualization example, the following values were set:
Dataset: TPCH orders
Visualization: Counter
Title:
Orders: Target amount vs. actual amount by date
Value:
Field:
avg(o_totalprice)
Value row number: 1
Target:
Field:
avg(o_totalprice)
Value row number: 2
Filter
Field:
TPCH orders.o_orderdate
SQL query: For this counter visualization, the following SQL query was used to generate the data set named TPCH orders_target
.
SELECT o_orderdate, avg(o_totalprice)
FROM samples.tpch.orders
GROUP BY 1
ORDER BY 1
Line visualization
Line visualizations present the change in one or more metrics over time.
Configuration values: For this line visualization example, the following values were set:
Dataset: TPCH orders
Visualization: Line
Title:
Average price and order year by order priority and clerk
X-axis:
Field:
o_orderdate
Transform:
Yearly
Scale Type:
Temporal
Axis title:
Order year
Y-axis:
Field:
o_totalprice
Transform:
Average
Scale Type:
Quantitative
Axis title:
Average price
Group by:
Field:
o_orderpriority
Legend title:
Order priority
Filter
Field:
TPCH orders.o_clerk
SQL query: For this bar visualization visualization, the following SQL query was used to generate the data set named TPCH orders
.
SELECT * FROM samples.tpch.orders
Heatmap chart
Heatmap charts blend features of bar charts, stacking, and bubble charts allowing you to visualize numerical data using colors. A common color palette for a heatmap shows the highest values using warmer colors, like orange or red, and the lowest values using cooler colors, like blue or purple.
For example, the following heatmap visualizes the most frequently occurring distances of taxi rides on each day and groups the results by the day of the week, distance, and total fare.
Note
Heatmaps can display up to 64K rows or 10MB.
Configuration values: For this heatmap chart visualization, the following values were set:
Dataset: TPCH orders
Visualization: Heatmap
X column (dataset column):
o_orderpriority
Y columns (dataset column):
o_orderstatus
Color column:
Dataset column:
o_totalprice
Aggregation type:
Average
X-axis name (override default value):
Order priority
Y-axis name(override default value):
Order status
Color scheme (override default value):
YIGnBu
SQL query: For this heatmap chart visualization, the following SQL query was used to generate the data set.
SELECT * FROM samples.tpch.orders
Histogram chart
A histogram plots the frequency that a given value occurs in a dataset. A histogram helps you to understand whether a dataset has values that are clustered around a small number of ranges or are more spread out. A histogram is displayed as a bar chart in which you control the number of distinct bars (also called bins).
Configuration values: For this histogram chart visualization, the following values were set:
Dataset: TPCH orders
Visualization: Histogram
X column (dataset column):
o_totalprice
Number of bins: 20
X-axis name (override default value):
Total price
Configuration options: For histogram chart configuration options, see histogram chart configuration options.
SQL query: For this histogram chart visualization, the following SQL query was used to generate the data set.
select * from samples.tpch.orders
Pie visualization
Pie visualizations show proportionality between metrics. They are not meant for conveying time series data.
Configuration values: For this pie visualization example, the following values were set:
Dataset: TPCH orders
Visualization: Pie visualization
Title:
Total price by order priority and clerk
Angle:
Field:
o_totalprice
Transform:
Sum
Axis title:
Total price
Group by:
Field:
o_orderpriority
Legend title:
Order priority
Filter
Field:
TPCH orders.o_clerk
SQL query: For this pie visualization, the following SQL query was used to generate the data set named TPCH orders
.
SELECT * FROM samples.tpch.orders
Pivot visualization
A pivot visualization aggregates records from a query result into a tabular display. It’s similar to PIVOT
or GROUP BY
statements in SQL. You configure the pivot visualization with drag-and-drop fields.
Note
For performance reasons, pivot tables only support rendering 100 columns x 100 rows.
Configuration values: For this pivot visualization example, the following values were set:
Dataset: TPCH lineitem
Visualization: Pivot
Title:
Line item quantity by return flag and ship mode by supplier
Rows:
Field:
l_returnflag
Columns:
Field:
l_shipmode
Cell
Dataset:
Field:
l_quantity
Transform: Sum
Filter
Field:
TPCH lineitem.l_supplierkey
SQL query: For this pivot visualization, the following SQL query was used to generate the data set named TPCH lineitem
.
SELECT * FROM samples.tpch.lineitem
Scatter visualization
Scatter visualizations are commonly used to show the relationship between two numerical variables. You can encode the third dimension with color to show how the numerical variables differ across groups.
Configuration values: For this scatter visualization example, the following values were set:
Dataset: TPCH lineitem
Visualization: Scatter
Title:
Total price and quantity by ship mode and supplier
X-axis:
Field:
l_quantity
Axis title:
Quantity
Scale type:
Quantitative
Transform:
None
Y-axis:
Field:
l_extendedprice
Scale type:
Quantitative
Transform:
None
Axis title:
Price
Group by:
Field:
l_shipmode
Legend title:
Ship mode
Filter
Field:
TPCH lineitem.l_supplierkey
SQL query: For this scatter visualization, the following SQL query was used to generate the data set named TPCH lineitem
.
SELECT * FROM samples.tpch.lineitem
Table visualization
The table visualization shows data in a standard table but allows you to manually reorder, hide, and format the data.
Note
Tables can display up to 64K rows or 10MB.
Configuration values: For this table visualization example, the following values were set:
Dataset: TPCH lineitem
Visualization: Table
Title:
Line item summary by supplier
Columns:
Display row number: Enabled
Field:
l_orderkey
Field:
l_extendedprice
Display as:
Number
Number format: $0.00
Field:
l_discount
Display as:
Number
Number format: %0.00
Field:
l_tax
Display as:
Number
Number format: %0.00
Field:
l_shipdate
Field:
l_shipmode
Filter
Field:
TPCH lineitem.l_supplierkey
SQL query: For this table visualization, the following SQL query was used to generate the data set named TPCH lineitem
.
SELECT * FROM samples.tpch.lineitem
Number formatting in charts
For most chart types, you can format numeric values for axis tick labels, data labels, and tooltips. To choose a formatting style, click the kebab menu to the right of the X Axis or Y Axis label in the chart configuration panel. Then, click Format to show formatting options.
The following charts support number formatting:
Area
Bar
Combo
Counter
Heatmap
Histogram
Line
Pivot
Scatter
Table (Legacy formatting)
You can choose from the following formatting options:
Type: None, Currency ($), Percentage (%)
Abbreviation: None, Compact, Scientific
Decimal places: Max, Exact, All, Number of places Optionally, you can include a group separator such as a comma.
Note
Formatting is available for various types of currency. After selecting Currency as the Type, use the drop-down selector to choose your preferred currency.