Create Metrics with Tableau Pulse

Tableau Pulse provides insights about your data based on metrics that you define. After you create a metric, you can add members of your organisation as followers, and they'll receive regular email or Slack digests about their data. This digest surfaces trends, outliers and other changes, keeping followers up to date on the data relevant to their work. To learn more about the data, these users can investigate a metric on Tableau Cloud and see how different factors contribute to changes in the data. These insights give them the information they need to make data-driven decisions without requiring them to do complex analysis in Tableau.

Pulse home page

Metric definitions and metrics

Behind every metric in Tableau Pulse is a metric definition. Viewers interact with metrics. Metric definitions specify the core metadata for those metrics.

Parent-child relationship between definitions and metrics

Metric definition: The set of metadata that functions as the single source of truth for all the metrics based on it. Defined by a user with a Creator, Site Administrator Explorer or Explorer (can publish) site role. The following table provides an example of the metadata captured by a metric definition.

Metric definition for Superstore Sales
Definition fieldExample value
NameSuperstore Sales
Measure and aggregationSum of Sales
Time dimensionOrder Date
Compared toPrior year
Adjustable metric filtersRegion, Category
Number formatCurrency
Value going up isFavourable

Metric: The interactive objects that sit in front of a definition. Created when users adjust filters or time options, which means that there can be many metrics based on a definition. Users follow and explore metrics to get insights. The following tables provide an example of the options configured for metrics. These options are applied on top of the core value that is specified by the metric definition.

Metric for Superstore Sales – Technology
Metric optionExample value
Time periodQuarter to date
FiltersCategory: Technology
Metric for Superstore Sales – Office Supplies
Metric optionExample value
Time periodYear to date
FiltersCategory: Office Supplies

To get started in Tableau Pulse, you create a metric definition that captures the core value that you want to track. At its most basic level, this value is an aggregate measure tracked based on a time dimension. The definition also specifies options such as the dimensions that viewers are able to filter by, the way the value is formatted and the types of insights displayed.

When you create this definition, Tableau automatically creates an initial metric and sends you to that metric's page. The initial metric created for a definition has no filters applied, but any time you or another member of your organisation adjusts the metric filters or time options in a new way, Tableau Pulse creates an additional metric.

People in your organisation follow metrics, not metric definitions. By following individual metrics, they get insights specific to the dimensions that matter to them. The definition exists in order to let you manage the data for metrics from a single parent object. If a field in your data source changes, you can update the definition to reflect this change, and all metrics based on that definition will also reflect the change.

Say that you're a member of a sales organisation, and that organisation needs to track metrics across different territories and product lines. In Tableau Pulse, you would create a metric definition that includes the core value of the sum of daily sales with adjustable metric filters for region and product line. Then, you would create metrics for each region and product line. Finally, you would add members of your organisation as followers to the metrics that cover where and what they sell.

What makes Tableau Pulse different

Tableau Pulse presents a simplified way to create metric definitions, so that with only a few selections, you can make a definition that would normally require complex calculations to build in traditional Tableau viz authoring. Members of your organisation use that metric definition as a jumping off point to make metrics relevant to their needs, by slicing the data based on different dimensions or time options. Because insights about these metrics are sent directly to followers, your colleagues get the data they need in their flow of work.

With Tableau Pulse, users have an easy, self-service way to take part in guided data exploration. They can ask suggested questions to see how different dimensions affect the data. This guided exploration complements the more free-form analysis that's possible with the traditional Tableau viz authoring experience and allows users unfamiliar with Tableau analysis to understand their data.

Questions and answers about metric data

Note that though some parts of Tableau Pulse are similar to other Tableau features, Tableau Pulse combines metrics and insights in an all-new experience. In February 2024, with the release of Tableau Pulse, Ask Data and Tableau's legacy Metrics feature were retired. Like Ask Data, Tableau Pulse lets you ask questions of your data, so you can learn the how and why behind the numbers you see. Tableau Pulse also lets you create and track metrics, like the legacy Metrics feature, but Tableau Pulse metrics don’t stand alone. These metrics are the source of insights about your data.

Data source requirements for metric definitions

You create a metric definition by connecting to a published data source. Make sure that the data source you're working with meets the following criteria.

  • It’s a single published data source. You can't connect to a data source that is embedded in a workbook, and you can't connect to multiple data sources or use data blending, unless you combine the data before publishing the data source. The data source can be an extract or a live connection, and it can use a virtual connection or connect directly to the data.
  • You have the Connect permission capability for the data source.
  • The data source contains:
    • A measure to be aggregated as a sum, average, median, maximum or minimum or a dimension to be aggregated as a count or count (distinct).
    • A time dimension for the metric's time series. Tableau Pulse monitors data over time, so single point-in-time values won’t produce a valid metric. The granularities supported for the time series are day, week, quarter and year. Data that requires a lower level of granularity (hour or minute) isn’t a good fit for Tableau Pulse.
    • At least one dimension that can be used to filter the data and insights.

Create a metric definition

After making sure that your data source will work with Tableau Pulse, you're ready to start creating your definition. The definition editor is optimised for larger screens, so you should create your definition using a desktop or laptop computer rather than a mobile device.

To create metric definitions, you need a Creator, Site Administrator Explorer or Explorer (can publish) site role on Tableau Cloud. If you have a Viewer site role, you can follow metrics and discover insights, but you can't create metric definitions.

  1. From the Tableau Pulse home page, select New Metric Definition.
  2. Select a data source to connect to, then select Connect.
  3. For the Name, enter a name that isn't in use by other metric definitions. This name appears on all metrics based on the definition, so choose a name that's easy for others to understand.
  4. For the Description (optional), provide brief details to help others make sense of the data. The description appears on the definition page. On the insights exploration page for each metric, the description shows when users select the info icon.

Define the metric value

  1. For the Measure, select the field to track. You can select a measure or a dimension, but dimensions must be aggregated as a count or count (distinct) so that they result in a measure that can be tracked.
  2. For the Aggregation, select how Tableau Pulse should aggregate the field you're tracking. If you require a more complex aggregation, see Create an advanced definition (optional).
  3. For Show sparkline values to date as, select whether you want the points on the metric chart to display as a running total or as non-cumulative values. The current value shown at the top of the metric will always be a running total for the period you're tracking. This setting applies to the sparkline, the overview line chart and applicable insights.
  4. For the Definition filters (optional), select values to limit the metric data. Definition filters affect the data for all metrics based on the definition and won’t be adjustable by the viewer. Fields added as definition filters change the meaning of the definition. For example, a definition filter might exclude returned orders to define net sales. If you simply want to use a field to segment the data, add an adjustable metric filter, available under the Options section. For more information, see Define metric options.
  5. For the Time dimension, select the field to define the time series.
  6. For Compared to, drag the time comparison that you want to be the primary comparison to the top of the list. The primary time comparison is displayed in digests and insights and on the metric overview card. The secondary comparison appears in addition to the primary when a user opens a metric on Tableau Cloud to view the insights exploration page. If you don't want a secondary comparison, select the x to remove it.

How fiscal calendars work with metrics

If your time dimension is configured to use a fiscal calendar, Tableau Pulse uses that calendar. The metrics based on a definition with a fiscal calendar will show fiscal years and fiscal quarters on charts and insights. When you create a definition, the fiscal start month is listed under the time dimension field, if one is set. You can't adjust the fiscal calendar in Tableau Pulse. To change it, edit the data source used by the definition. For more information, see Fiscal Dates.

Support for fiscal calendars was added in February 2024. The Tableau Pulse beta didn't support fiscal calendars. If you created metrics during the beta period, and your data uses a fiscal calendar, those metrics won't automatically update to reflect the fiscal calendar. You'll need to adjust the date range to create new metrics that use the fiscal year. Then remove the followers from the metrics that used the old calendar and add them to the newly created metrics.

Create an advanced definition (optional)

If you prefer the flexibility of working in the traditional Tableau viz authoring environment, or if you need to create calculated fields, use the advanced analytics editor.

  1. On the definition panel, select Create Advanced Definition.
  2. Add fields to the measure, time dimension and filters shelves. Only the fields or calculations that you add to these shelves will be saved by the editor.
  3. Select Apply. The fields you added in the editor replace the equivalent fields in the definition panel. To edit these fields, reopen the editor. You can't edit fields configured in the advanced analytics editor in the definition panel.

Define metric options

  1. For Adjustable metric filters, add at least one option. These filter options appear on metrics and allow users to scope the data to meet their needs. Adjusting these filters creates additional metrics from a definition. The fields you add as adjustable metric filters also determine the dimensions used to generate insights about the data.
  2. For the Number format, you can specify custom units to show for the value, or you can set the value to display as currency or as a percentage.

Configure insights

  1. Select the Insights tab.
  2. The fields under Insight dimensions are the same fields that you added as adjustable metric filters. Tableau Pulse uses these dimensions when monitoring your data to surface relevant insights, as shown in the insights preview.
  3. For Value going up is, select whether the change is neutral, favourable or unfavourable. This option controls the colour for the change value: blue for neutral, green for favourable and red for unfavourable. It also affects the language used in insights that refer to the change.
  4. Under Insight types, select the menu, then select Turn Off to adjust the types of insights shown. Hover over the info icon for a description of each type.
  5. Verify that the metric and insights previews look as expected, then select Save Definition. Tableau Pulse creates the definition along with the initial metric based on that definition, which has no adjustable metric filters applied. You can find your definition under the Browse Metrics tab on the Tableau Pulse home page.

For an overview of insight types and the insights platform, see The Tableau Pulse Insights platform and insight types in this topic.

Create metrics

After you create your definition, you’ll be taken to the initial metric for that definition. This page is the insights exploration page for that metric. On it, you can see insights based on dimensions that you select, and you can create more metrics by adjusting filters.

  1. On a metric for your definition, select Adjust. The filter labels become interactive.
  2. Select the buttons to change the time and filter options.
  3. Select the tick button. If a metric with that combination of filters doesn’t yet exist, Tableau Pulse creates one.

To learn how viewers interact with these metrics, see Explore Metrics with Tableau Pulse.

Edit a metric definition

If your data source changes, and the metrics that are based on it break, edit the metric definition to account for these changes. Any changes that you make to the definition will affect all metrics based on it.

  1. Open a metric for the definition you want to edit.
  2. Select the actions menu, then select Edit Definition.

    Edit definition button

How editing filters on a definition affects metrics

When you edit a definition, if you remove an adjustable metric filter or add a definition filter that excludes the value used in a metric filter, metrics using that filter won't be deleted. Followers of those metrics will be able to adjust the affected filter and add other followers, but users who aren't already followers won't be able to follow those metrics on their own.

To make it so users no longer see metrics that are based on eliminated filters, remove the followers from those metrics. Alternatively, if you want to get rid of all of the metrics for a definition, delete the definition.

Delete a metric definition

Deleting a metric definition also deletes all of the metrics based on it.

  1. On the Tableau Pulse home page, select the Browse Metrics tab.
  2. On the metric definition that you want to delete, select the actions (...) menu, then select Delete.

Manage followers

Followers are specific to each metric, not to the metric definition as a whole. That way, individuals in your organisation receive insights about only the metrics that matter to them. Any time you create a new metric, you need to add followers. Followers don’t carry over from the previous metric that you were viewing.

Add followers

  1. Open the metric that you want to add followers to.
  2. Select the Followers button.
  3. In the search box, enter the name of the user or group that you want to add.
  4. Select Add.

If users are added to a metric as part of a group, they won’t be able to remove themselves individually. If you want users to have control over the metrics they follow, add them as individuals.

Remove followers

  1. Open the metric that you want to remove followers from.
  2. Select the Followers button.
  3. Next to the follower's name, select Remove.

To get a head start when creating a metric definition, you can create one from the list of recommended metrics shown for dashboards.

  1. While viewing the dashboard that you want to create a metric definition from, select the Data Guide button in the toolbar.
  2. On the dashboard, select the viz with the data you want to use. Data guide shows recommended metrics for this viz. Depending on how well the data in the viz fits the requirements for a metric, you might not see recommended metrics. If data guide can't recommend a complete metric, it might show recommended measures or dimensions or the primary data source used for you to connect to.

    The Data Guide pane showing recommended metrics
  3. Select a recommendation to configure it in Tableau Pulse.
  4. The recommendation is pre-populated in the Tableau Pulse definition editor. To finish setting up your definition, see Create a metric definition.

Embed metrics

You can use the Embedding API to embed Tableau Pulse metrics in web pages. For more information, see Embed Tableau Pulse.

The Tableau Pulse Insights platform and insight types

When you create a metric in Tableau Pulse, you also automatically get the insights that Tableau Pulse detects for each metric.

The Insights platform in Tableau Pulse detects drivers, trends, contributors and outliers for metrics. It proactively flags and describes insights that matter using natural language and visual explanations. The top insight for each metric is displayed with the metric.

Tableau Pulse also provides a path to further explore data by surfacing questions for the insights that it detects for a metric. This guided question-and-answer experience progressively reveals insights in the context of the metric. As you and others click through the suggested questions about the data, answers are revealed in easy-to-read charts with insights about the underlying data.

For more information, see Tableau Pulse: Proactive Answers to Your Common Business Questions with Automated Insights(Link opens in a new window).

Insight summaries highlight metrics of interest

When Tableau AI is turned on and you or others follow two or more metrics, Tableau Pulse provides an overview to help you quickly see the latest insights across your metrics of interest. This insights summary appears at the top of digests and in the Tableau Pulse home page.

Tableau Pulse looks across the metrics that you follow and leverages Tableau AI to summarise the most significant changes. Period Over Period Change and Unusual Change are the insight types considered for insight summaries.

Insight summaries use a large language model (LLM) to provide a personalised overview in plain language. Tableau AI is built on the Einstein Trust Layer, meaning it enables trusted, ethical and open AI-powered experiences without compromising data security and privacy. For more information, see Tableau AI in Tableau Pulse(Link opens in a new window) and Einstein Generative AI for Tableau(Link opens in a new window).

Types of insights detected by Tableau Pulse

The questions users typically ask about metrics can be grouped into well-known patterns of analysis: descriptive, diagnostic, predictive and prescriptive.

  • Descriptive questions: What happened to my Metric?

  • Diagnostic questions: Why did it happen?

  • Predictive questions: What is likely to happen next?

  • Prescriptive questions: What actions should I take?

The Insights platform in Tableau Pulse focuses on helping users answer basic descriptive questions they have about their metrics, such as:

  • How much has a metric value changed since the last period or the same period last year?

  • How is a metric trending over time?

  • Which members of a dimension contribute most to a metric value?

  • What other dimensions are driving a metric value in a favourable direction?

Insights in Tableau Pulse can alert users to hidden changes or anomalies in Tableau Pulse Metrics so they can better diagnose issues. For example:

  • Is the metric value higher or lower than normal?

  • Is the metric value unusually concentrated in a few entities of a dimension?

  • Has the trend of the metric changed recently?

  • Are there any unusually large records or outliers that are impacting the metric value?

Insight types in Tableau Pulse

The following insight types are used in Tableau Pulse:

Insight TypeDescriptionConfigurable?
Period Over Period Change

Shows how a metric has changed between two periods.

This insight is displayed as part of every metric.

Always on by default

Tableau Pulse considers the Period over Period Change insight for insight summaries.

Top Contributors

Shows the highest values in a dimension for a metric within a given time range.

A top contributor is a dimension member that ranks in the top N in contribution to the scoped metric’s value, aggregated on a specified time range.

Always on by default

Tableau Pulse uses the Top Contributors insight in metrics for breakdowns.

Bottom Contributors

Shows the lowest values in a dimension for a metric within a given time range.

A bottom contributor is a dimension member that ranks in the bottom N in contribution to the scoped metric’s value, aggregated on a specified time range.

Can be turned on or off in the Insights tab in metric definition settings

Concentrated Contribution Alert (Risky Monopoly)Shows when a small number of dimension members make up a majority (50% or more) of the contribution to a metric.Can be turned on or off in the Insights tab in metric definition settings

Top Drivers

Shows values for dimension members that changed the most in the same direction as the observed change in the metric.

Can be turned on or off in the Insights tab in metric definition settings

Top Detractors

Shows values for dimension members that changed the most in the opposite direction to the observed change in the metric.

Can be turned on or off in the Insights tab in metric definition settings

Unusual Change

Shows when the value of a metric for a given time range is higher or lower than the expected range based on historic observations of the metric.

Always on by default

Tableau Pulse considers the Unusual Change insight for insight summaries.

Current Trend

Shows current trends to communicate the rate of change, direction and fluctuations for the metric value.

Can be turned on or off in the Insights tab in metric definition settings

Trend Change Alert

Shows new trends that vary significantly from the current trend. This insight communicates the rate of change, direction and fluctuations for the metric value.

Can be turned on or off in the Insights tab in metric definition settings

How Tableau Pulse generates and maintains trusted insights

Here are a few ways the Insights platform generates automated business insights users can trust:

  • Tableau Pulse Insights Service starts by using standardised, deterministic statistical models to detect facts about metrics that are guaranteed to be accurate. These facts act as the ground truth when generating insights.

  • Every insight that is generated is restricted to the data security context (such as RLS settings) of the user who made the request. This approach ensures users can only see the data they're authorised to see.

  • Analysts can enable or disable different insights being detected for a metric so they can control what is delivered to their users.

Here’s how Tableau Pulse brings it all together: the Insight platform statistical service uses the analytical context of the metric being followed or viewed to run automatic statistical analysis that generates facts about the metric. These facts answer the different questions using the user's data security context.

For insight summaries, the most relevant facts are processed by Tableau AI. These facts are used as ground truths to contextualise language generation. Insight summaries are generated using natural language grounded in statistical truths. The resulting facts generated are bundled together and surfaced in several features throughout Tableau Pulse as insight summaries when Tableau AI is turned on for a site.

How the Insights platform determines relevance

To reduce noise, Tableau Pulse only surfaces the most relevant, useful insights – and avoids displaying noisy or spurious findings. The Insight platform considers the following factors to ensure the insights users see are relevant and useful:

  • The analytic context for insights is based on the Tableau Pulse metric definition. Unlike other solutions that look for insights across all columns in the data, the Insights platform restricts its analysis to the measures and dimensions referenced by the metric definition, as curated by analysts. In addition, only the filtered context of the metric user is viewing or following is considered when generating insights.

  • Insights are ranked based on impact to the metric. Each fact detected by the Insights platform is scored based on the impact it has on the metric value. Only the facts determined to be most statistically impactful to the metric value are returned first.

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