Visualizations

Imply provides a wide array of expressive visualizations that enable fast, interactive exploration of your data. Visualizations are not just static charts. You can interact directly with them by clicking on various graphical elements to select data segments for drill-down and deeper analysis.

When you change the shown dimensions, Pivot chooses the best visualization for the selected dimensions automatically.

To choose a visualization, click on the current visualization type to the right of the filter and split bars. The following example shows Table as the current visualization:

The following sections describe the available visualizations.

Overall

The default visualization is the overall visualization. It presents a numeric summary of the currently selected measures, applying any selected filter criteria.

You can select multiple measures and show a time range comparison. The following example shows the number of deleted events in the latest hour compared to the previous period:

Conditional formatting

If you create an overall visualization with a single measure, you can apply conditional formatting to color the visualization as an indication of data severity—green for ok, amber for warning, red for critical.

To add conditional formatting, click the paintbrush icon in the visualization pane on the right, then click Add condition. Select the condition to apply to the data and the corresponding formatting. You can create multiple conditions.

You can also create a condition based on a comparison. In the following example, the amber color of the visualization indicates that the absolute change in number of deleted events for the previous hour was more than 5,000:

If you add an overall visualization tile with conditional formatting to a dashboard page, the colored icon next to the page name indicates the severity of the data on the page. See Dashboard pages for more information.

Overall (beta)

A new overall visualization includes a trend line and an updated properties panel.

info

Before you can use the beta overall visualization, you must enable the SDK based visualizations feature flag with "overall" in the array. For example, ["flat_table","gauge","overall","time_series"] enables this and other SDK-based visualizations. See Feature flags for more information. Once enabled, the new overall visualization replaces the standard overall visualization.

The following example shows the number of events deleted in the latest hour compared to the previous period, with conditional formatting:

Bubble chart

The bubble chart visualization lets you examine the relationship between two or three numeric variables. Each bubble in the chart corresponds to a single data point, and the measures for each point are indicated by the x-axis (the first measure), the y-axis (the second measure), and bubble size (an optional third measure).

The following example shows a bubble for each of the five channels in the filter. The bubble's horizontal position notes the number of events added to the channel during the latest six hours, and the vertical position notes the number of events deleted from the channel during the same period. The bubble size indicates the relative comment length for the channels.

Flat table

The flat table visualization is similar to the table visualization but it displays flattened data instead of nested data.

info

Before you can use the flat table visualization, you must enable the SDK based visualizations feature flag with "flat_table" in the array. For example, ["flat_table","gauge","overall","time_series"] enables this and other SDK-based visualizations. See Feature flags for more information.

Select one or more Columns to Group data by and any additional Columns to display. For columns that contain URLs, hold Cmd (or Ctrl) and click the URL to open it in a new tab. You can select what to display when a column contains multiple values. Select a Pivot column and one or more Measures and the visualization displays a column for each combination.

The following example shows the Number of Events for City: Chicago in the Koalas to the Max data cube. The data is grouped by Agent category and Browser. The table shows the additional column Event Type. Where Event type contains multiple values, Pivot displays the latest value.

Gauge

The gauge visualization displays a summary of a selected aggregate as a gauge.

info

Before you can use the gauge visualization, you must enable the SDK based visualizations feature flag with "gauge" in the array. For example, ["flat_table","gauge","overall","time_series"] enables this and other SDK-based visualizations. See Feature flags for more information.

The gauge shows a number or percentage proportional to the Min and Max values you set. You can color specified ranges, set a custom label, and show a legend.

The following example shows the number of events for the latest day in the Demo data cube, proportional to the maximum 500,000. The legend shows four colored numeric ranges.

Geo marks

The geo marks visualization is the natural choice for dimensions that represent geographically encoded data. It can work with country encoded data. To use geo-oriented visualizations, modify the data cube configuration to make the country encoded data to be Geo type.

Geo shade

The geo shade visualization (also known as a Choropleth map) is another choice for dimensions that represent geographically encoded data. It can work with country encoded data. To use geo-oriented visualizations, modify the data cube configuration to make the country encoded data to be Geo type.

Heatmap

The heatmap is a visualization that shows two dimensions as a 'matrix'. It is similar to the grid visualization and it works particularly well when one or both of the dimensions are continuous.

Horizontal bars

The horizontal bars visualization shows each dimension in horizontally-oriented time buckets.

Line chart

The line chart visualization is designed to demonstrate a trend over time. It's useful for showing temporal dimensions.

The following example line chart displays two measures—Number of Events and Session Length—over time for four Country values.

You can display two continuous metrics on the same chart with two axes. To do this, select two measures and then click the paintbrush icon in the right pane. Select Show measures in: Cell and Dual axis: Yes.

The following example line chart displays the same Number of events and Session length measures over time as the above chart. On the dual axis chart, the data for the four selected countries displays as a single line for each measure.

Markdown

You can use a Markdown tile to add formatted text to a dashboard. For more information, see Managing dashboards.

Records

The records visualization shows the raw data underlying the data cube, allowing you to see all dimensions that are in each record. This view can be useful for certain debugging issues. You can also view your records in groups for specific values of one or more dimensions by adding the dimensions to the show bar.

Records table

The records table visualization shows the raw data underlying the data cube, in table format. To filter the data, click any value in the table and select Exclude.

Sankey

The Sankey visualization shows the flow from one set of values to another. In Sankey diagrams, the width of each connection is proportional to the flow volume between the values.

Sparkline

In contrast to the line chart visualization that displays lines for multiple dimensions on a single chart, the sparkline visualization displays multiple line charts—one for each dimension.

The following example sparkline chart displays the number of events over time for five Country Name values:

Hover over the first column heading—Country Name in the above example—to display the Swap axes icon. Click the icon to swap the splits assigned to the axes.

Spot matrix

The spot matrix shows the distribution of events on a two dimensional matrix using circles, with larger circles representing a greater number of events.

Stack area

The stacked area chart is similar to the line chart, and can be used in similar situations. Unlike the line chart, the area chart lets you see what all the values add up to together. This lets you see the overall trend, while also showing the individual contributions of different dimensions.

Street map

If your event data contains latitude and longitude coordinates, you can use the street map visualization to pinpoint events to precise locations on a map.

If your Imply deployment is on-prem, contact your Imply support representative to enable the street map visualization.

Create dimensions for your latitude and longitude data. Add the dimensions to the show bar and select Street map from the visualization selector on the right side of the page.

You can click the paintbrush icon to change the default Grid display to Blobs, for a circular representation of the data. The darker the grid or blob color, the higher the concentration of events at that location. Click anywhere in a grid or blob to see the corresponding latitude and longitude coordinates and the number of related events. Click Filter to filter the event display by specific latitude and longitude coordinates.

Sunburst

The sunburst (also known as a donut or pie chart when using only one split) is a visualization that represents the ratios between the values of a dimension. When rendering multiple dimensions, each is subdivided to show proportional representation.

Table

The table visualization is the default view for a categorical (string) dimension. It presents a table view of the data with formatting that aids visualization of measure magnitude.

The table visualization can show multiple dimensions, as well as multiple measures, as columns. For columns that contain URLs, hold Cmd (or Ctrl) and click the URL to open it in a new tab.

The following example shows the number of Wikipedia events for City Name London or New York by Channel for the latest 6 hours, with a comparison to the previous period:

Click the paintbrush icon on the right to access layout options. Pivot displays a nested layout by default—shown above. Click and drag the dimensions in the show bar to rearrange their order and change the nesting.

Hover over the first column heading—City Name > Channel in the above example—to display the Swap axes icon. Click the icon to swap the splits assigned to the axes.

Select the Flat row layout to display a column for each dimension.

The Overall rows display the dimension totals. In the above example, there are 10 events that match the applied filters—9 for the #en.wikipedia Channel and 1 for #pl.wikipedia. Of the 9 #en.wikipedia events, 5 are for City Name London and 4 are for New York.

Time series

The time series visualization allows you to use time series functions to generate a line or bar chart showing the rate of change in your data.

info

Before you can use the time series visualization, you must:

• Load the imply-timeseries extension. See Time series functions: Setup for more information.
• Enable the SDK based visualizations feature flag with "time_series" in the array. For example, ["flat_table","gauge","overall","time_series"] enables this and other SDK-based visualizations. See Feature flags for more information.

Set the following properties in the visualization:

• Render type: Line chart or bar chart.
• Timeseries function: Select TIMESERIES to create a time series of the data points, or another time series function from the drop-down list.
• Time column: Time column to display on the x-axis.
• Additional Data columns: One or more columns Pivot applies the time series to—the columns Pivot displays depends on the selected function. Data columns display on the y-axis.
• Interpolator: You can specify the method to interpolate missing data points in the time series:
  • Linear: Use linear interpolation to fill the missing data points.
  • Padding: Carry forward the closest value in the series.
  • Backfill: Carry backward the closest value in the series.
• Timeseries bucket: Choose a segment period for Pivot to use when calculating interpolation points.
• Group by: Column to represent as lines or bars in the visualization.
• Group limit: Limit to apply to the group column.

If Pivot displays a message that the selected window of times contains too many entries to display, adjust the filter to reduce the number of entries.

The following example visualization applies the TIMESERIES function to a Koalas to the Max data cube. The data is filtered to a specific period. The time column on the x-axis is Time, with Number shown on the y-axis. The data is grouped by Browser. The visualization displays the top three browsers with the largest number of events. There's a point on the chart for every 5 minutes as set in the time series bucket.

Treemap

The treemap allows you to see how the values of a dimension combine to make up the whole. It is particularly suitable for hierarchical dimensions.

Vertical bars

The vertical bars visualization shows each dimension in vertically-oriented time buckets.