Create an Overlay

Create an overlay

1. In a project, on the navigation bar, click Model > Analytic Objects.
2. Click Create Analytic Object.
3. In Analytic object type, select Overlay.
4. Type a display name and description.
5. When finished, click Create.

To configure an overlay, do the following:

1. Create properties in the overlay. Properties in Visier should align with data for the overlay; for example, the Overall Score property in the Engagement overlay should align with engagement score data from the source file's column. For more information, see Properties.
2. Create dimensions in the overlay. Dimensions in Visier should align with data for the overlay; for example, the Engagement Location dimension in the Engagement overlay should align with location data in the engagement source file. For more information, see Dimensions.
3. Do one of the following:
   • Create and configure member maps. Member maps connect overlay-specific dimensions to corresponding dimensions in other subjects or events; for example, you can map Location Hierarchy and Organization Hierarchy to an Engagement overlay by creating the member maps Engagement Location Comparison and Engagement Organization Comparison and mapping those hierarchies to the Engagement Location and Engagement Organization dimensions. For more information, see Create a Member Map.
   • Connect a shared dimension to the overlay. Shared dimensions connect overlay data to subject or event data that contain matching dimension members. For more information, see Create a Leveled Dimension or Create a Parent-Child Dimension.

     Tip:  

     • If your overlay data doesn't match the subject or event data, use a member map. For example, if the Gender values in the overlay are M and F but the Gender values in the Employee subject are Man and Woman, use a member map.
     • If your overlay data matches the subject or event data, use a shared dimension. For example, if the Gender values in the overlay are M and F and the Gender values in the Employee subject are also M and F, use a shared dimension.
4. Map data values to attributes in the overlay. Each overlay has mandatory attributes and optional attributes that are mapped to columns in the overlay data; for example, the EventDate attribute is mapped to the Date column in the overlay source data. For more information, see Mappings.
5. Define the settings in the overlay. Each overlay has settings such as the time model and aggregation type; for example, engagement data is subject-like and aggregated using lookup behavior. For more information, see Overlay settings below.

Overlay settings

The overlay settings allow you to modify its categorization and treatment of values.

Tags

Tags are user-defined categories that group content in the solution. A tag can apply to multiple object types, including analytic objects, metrics, and guidebooks. A user may filter for objects with a particular tag throughout the solution. For this setting, add tags to identify the object as part of a specific content category. For more information about tags, see Create and Assign Tags to Content.

Time model

The time model defines how overlay values are handled. This setting primarily defines what values are shown when selecting multiple time periods in the solution. This depends on whether the overlay holds event values or subject values.

When selecting multiple time periods, one expects event values to be aggregate but only the latest subject value to be shown. The platform generalizes this split with two options for the time model. Use:

• Each value equals a period for event values.
• Each value equals an interval for subject values.

An overlay value equals a period when it represents an event, such as the Expenses overlay, which represents the aggregated values of expense events. These values are valid for an instance but the platform displays them for the period of the granularity of the overlay.

An overlay value equals an interval when it represents a subject, such as the Engagement overlay, which represents the aggregated values of engagement for the Employee subject. These values represent the state of a subject and is valid over an interval.

Aggregation

There are two options for overlay aggregation: rollup and lookup. The types define how the values aggregate in a hierarchy.

• Rollup: Non-leaf intersections in the overlay are derived from their descendants. Select rollup if the values can be aggregated.
• Lookup: Every intersection in the overlay has a value that is individually provided and retrieved. Select lookup if the values cannot be aggregated.

Overlay category

The overlay category defines the type of data for the overlay. For this setting, refer to the following overlay categories and their definitions to choose the one you need.

• Business outcome: Defines KPI data for historical or correlation analysis.
• Plan/budget: Defines future goals or plans.
• External benchmark: Defines known values that are externally collected, government-provided, or internally generated.
• Visier Benchmark: Defines aggregated data provided by Visier that is appended to the tenant data version. Only applicable to Visier-generated overlays.
• Other: No category is defined.

Data version settings

Visier allows each analytic object to override the globally-defined end date.

The end date config type sets the upper limit of selectable time periods in the solution experience. For example, if the end date config type is End of previous month and the current month is February, your users can select data up to the end of January in analyses and visualizations.

You can set the end date config type at the tenant level and per analytic object.

• Tenant level: The end date config applies to all analytic objects.
• Per analytic object: Overrides the tenant end date config for a specific analytic object.

To override the tenant end date config type for a specific analytic object: 

1. In a project, on the navigation bar, click Data > Tenant Settings.
2. Select a data category.

3. In Settings, turn on Enable end date overrides on individual analytic objects.

   Tip: If disabled, all analytic objects use the latest upload to determine the data end date. If enabled, each analytic object uses the latest upload for data that populate the object. For objects that aren't updated frequently, we recommend that you set object's end date config type to Use timestamp of source for a specific analytic object.

   Let's say you loaded Employee Engagement data on July 31 and Employee data on September 20. Enable end date overrides on individual analytic objects is turned on, but there are no overrides for Employee Engagement or Employee specifically. Both objects use the tenant-level end date config type, but Employee Engagement uses July 31 as the latest upload, whereas Employee uses September 20 as the latest upload. If the tenant-level end date config type is End of previous month, then Employee Engagement's end date is June 30 and Employee's end date is August 31.

4. On the navigation bar, navigate to Model > Analytic Objects.
5. Select an analytic object.
6. In Settings, under Data version settings, turn on Use default.
7. In End date config type, select an end date config type from the list.

The following table describes each of the end date config types. To illustrate each end date config type's behavior, the example columns show what date is available to select if today is June 29, 2017 but the latest upload was April 30, May 2, or June 9.

End date config type	Description	Example 1:  Latest upload on April 30	Example 2: Latest upload on May 2	Example 3: Latest upload on June 9
Auto detect from data	Use the date of the latest data point in the upload, including dates in the future. For example, let's say the latest data point in each example upload is April 30, July 1, and June 30, respectively. We recommend Auto detect from data as the default tenant-level end date config type.	April 30	July 1	June 30
End of current month	Use the end of the month of the latest upload.	April 30	May 31	June 30
End of previous day	Use the end of the latest upload minus one day.	April 29	May 1	June 8
End of previous week	Use the last Sunday of the latest upload.	April 23	April 30	June 4
End of previous month	Use the last day of the previous month of the latest upload.	March 31	April 30	May 31
Use source timestamp	Use the exact time of the latest upload.	April 30	May 2	June 9
Use timestamp of source for a specific analytic object	Use the exact time of the latest upload that contains the data for a specified analytic object. For example, use the time of the latest upload for Employee data. Let's say the latest Employee upload was on March 8.	March 8	March 8	March 8
Use timestamp of current run	Use the current time.	June 29 (current time)	June 29 (current time)	June 29 (current time)
End of current day	Use the end of the current date.	June 29 (end of day)	June 29 (end of day)	June 29 (end of day)
End of previous month (if first load of month) or previous day	Use the last day of the previous month if it's the first upload of the month. For all other uploads, use the end of the previous day. For example, let's say that April 30 isn't the first upload of the month, May 2 is the first upload of the month, and June 9 isn't the first upload of the month.	April 29 (end of previous day)	April 30 (end of previous month)	June 8 (end of previous day)
End of previous month (if first load of month) or week	Use the last day of the previous month if it's the first upload of the month. For all other uploads, use the end of the previous week. For example, let's say that April 30 isn't the first upload of the month, May 2 is the first upload of the month, and June 9 isn't the first upload of the month.	April 23 (end of previous week)	April 30 (end of previous month)	June 4 (end of previous week)
End of previous month (if first load of month) or use source timestamp	Use the last day of the previous month if it's the first upload of the month. For all other uploads, use the exact time of the latest upload. For example, let's say that April 30 isn't the first upload of the month, May 2 is the first upload of the month, and June 9 isn't the first upload of the month.	April 30 (time of latest upload)	April 30 (end of previous month)	June 9 (time of latest upload)
End of current month (if last day) or previous month	Use the end of the month of the latest upload if it's the last day of the month. If it's any other day of the month, use the last day of the previous month.	April 30 (end of current month)	April 30 (end of previous month)	May 31 (end of previous month)
End of previous month (if first load of month) or current month	Use the last day of the previous month if it's the first upload of the month. For all other uploads, use the last day of the current month. For example, let's say that April 30 isn't the first upload of the month, May 2 is the first upload of the month, and June 9 isn't the first upload of the month.	April 30 (end of current month)	April 30 (end of previous month)	June 30 (end of current month)
Allow future data	Use the furthest date in the upload. For example, let's say there is a future start date of July 1 in all example uploads. Caution: Do not use for subject and overlay data.	July 1	July 1	July 1
Last specified day of the week	Use the latest week day, as specified, of the latest upload. For example, use the latest Wednesday of the latest upload.	April 26 (latest Wednesday)	April 26 (latest Wednesday)	June 7 (latest Wednesday)
Later or last specified day of the week or end of previous month	Use the latest week day, as specified, of the latest upload without going beyond the previous month. For example, use the latest Wednesday of the latest upload without going beyond the previous month.	April 26 (latest Wednesday)	April 30 (end of previous month)	June 7 (latest Wednesday)
End of current month (if within five business days to end) or previous month	Use the end of the current month of the latest upload if the upload is within five business days of the end of the month. Otherwise, use the last day of the previous month of the latest upload.	April 30 (upload is within 5 days from end of month, use end of current month)	April 30 (upload isn't within 5 days of end of month, use end of previous month)	May 31 (upload isn't within 5 days from end of month, use end of previous month)
End of previous month (if first load of month) or last specified day of the week	Use the last day of the previous month of the latest upload if it's the first upload of the month. Otherwise, use the latest week day, as specified. For example, use the latest Wednesday of the latest upload. In this example, let's say that April 30 isn't the first upload of the month, May 2 is the first upload of the month, and June 9 isn't the first upload of the month.	April 26 (latest Wednesday)	April 30 (end of previous month)	June 7 (latest Wednesday)

Default metric

The default metric associated with an analytic object is used to generate system alerts and prevent an empty state for charts when your users switch between dimensions that have no relationship to the metric.

If enabled on a subject, default metric allows you to view the subject's history in Detailed View.

After onboarding data, the default metric is an easy way to quickly verify that the data for an object was loaded as intended. For this setting, select a metric that will act as the default metric for the object in visualizations and will be available as a data overview in the studio experience dashboard.

Support value property

The support value property is an optional setting for benchmark overlays. A support property must be defined in the overlay to use best-fit functionality with benchmark values. This works as a tie breaker if multiple slices have the same number of valid records. The best fit works best with base metrics on lookup overlays and is thus optional for rollup overlays.

An overlay with a support value property set will return the most specific population—that being the smallest value of the support value property. For this setting, select a benchmark property to be the support value property.