Jen, the planner at ABC Corporation, is working with her team to create a forecast income statement for 2025. But first, she has been asked calculate projected labor expenses for that year.
After completing this lesson, you will be able to:
Jen, the planner at ABC Corporation, is working with her team to create a forecast income statement for 2025. But first, she has been asked calculate projected labor expenses for that year.
A data action is a flexible planning tool for making structured changes to planning data in SAP Analytics Cloud. Modelers design data actions and that planners run in stories or schedule them in the calendar.
A data action is created based on a planning model and consists of one or more steps that are carried out on a public or private version.
Data actions are used to process mass amounts of data.
Some use cases for data actions include the following:
Some features of data actions include the following:
Data actions can be created from the Navigation Bar or from Files.
Recent data actions will also show in the Recent Files section of your home screen.
The following types of action steps are available:
Setting parameters result in prompts when they're run in a story. Prompts are like variables, in that they make the data actions flexible and dynamic.
When a data action is executed from a story, as in the following example, the parameters related to the data action prompt you for source and target data.
Parameter Values are determined by:
Parameters Type can be based on members or numbers:
Member: Creates a parameter that represents a dimension member. For example, this type of parameter lets you change the year that you're copying data to or from.
Number: Creates a parameter that has a numeric value. For example, this type of parameter is added to advanced formulas, and can let you prompt users for values such as growth rate or gross margin percentage.
The Model assignment:
Data actions can be executed multiple ways:
In this section, we will focus on using the SAP Analytics Cloud calendar to schedule the data action as a task.
Using the calendar, you can schedule a data action. If a data action takes a few minutes to run, you can schedule it to run at night.
Before the data action runs, its status will be Open.
After it runs with no issues, the status will be Successful.
If something goes wrong, the status will be Failed.
When scheduling a data action, prompts must have assigned parameter values.
Data actions can be used in other data actions that belong to the same model.
For example, you create a data action that calculates subscription revenue based on booking data, with a dynamic parameter for the product type. Using embedded data action steps, you can reuse that data action multiple times in another data action and you can specify a different product type each time.
This lowers the cost of development and maintenance.
Here are some other features of embedded data actions:
When data actions are scheduled from the SAP Analytics Cloud calendar or executed from a story, you can use the Data Action Monitor to check the status.
The data action monitor shows:
You wish to check the status and details for the data action that was created to calculate labor and benefits.
In this practice exercise, you will:
Copy actions allow you to copy data from one set of members to another, specifying options for filters and aggregation. For example, you can copy data for a product in one region to another product in other regions.
In the following example, the data action is set up to copy data by version and year at the same time. For example, copy the 2023 actual data to the 2024 plan data.
The copy rule doesn't allow the use of version, so there are two key points to remember:
Every data action has a system-provided Filter for Version. The default version filter is the target version prompt.
In the Aggregate To area of a data action, add any dimension where you want to override the default disaggregation behavior.
For dimensions that aren't included in the Aggregate To area, the copied data will match the distribution of the source data by default. This behavior is similar to copying and pasting a cell with the Paste Details option enabled.
For example, if you want to remove the distribution of data to different customers for privacy reasons, you can aggregate the data to the Unassigned member of the Customer dimension. In this case, all of the copied data is booked to the Unassigned member.
In order to copy data from one year to another and at the same time copy actual to plan:
When Data Action Triggers are added to stories, they appear as push buttons and can be configured using the right panel.
The prompts are based on the data action parameters. In a story, these are the input options:
If you choose the Prompt type, there are four Value options:
When a data action is run by selecting the push button in the story, a prompts dialog allows for dynamic member selection.
If the data action is set to always run in the background, or if you select Run in Background after starting it, you'll return to your story or extended story. You can keep working with your story or extended story but you'll have to wait until the data action finishes to make changes to the same version and you may need to refresh to see the results.
A message appears when it’s complete or you can check the Notifications list for the results.
Data actions can be set up in stories to publish automatically, so that planners don't have to publish data in a separate step. Alternatively, if a data action is set up in a story to not publish automatically, then the data can be reverted.
In the second part of this process, Jen must develop the rough cut labor forecast. To get started, she needs to copy the labor hours and rates.
Data is often needed from several sources to perform the planning process, for example, prices are in one model but the income statement data is in another. Depending on the circumstances, the data may need to be physically copied while in other cases, a look-up will suffice.
Before we get into the specifics of copying data between models, let's consider the options when working with data in multiple models:
In the Mapping area, set how the data will be mapped from the source model to the dimension members of the target model.
For each of the target dimensions listed in this area, you need to either map a source dimension or select a default value. In the following image, you can see that currency is set to Unassigned. In this example, labor hours are being copied from an HR into an expense model. In the HR model, labor hours are not related to currency.
You don't need to map source dimensions that aren't relevant for the target model. For example, you might choose not to map gender or office location from the Headcount model to the Finance model.
The source and target models can have different dimensions. For example, HR has personal area but Expense does not. In the data action, a constant can used for personal area.
When data is copied from a weekly to a monthly model, the data is aggregated from weeks into months. The assignment of a week that begins in one month and ends in another is based on the Auto-Generation Strategy in the data action.
When mapping date dimensions with different time granularity, the first day of the source member will always be used as a point of reference. For example, this option could be used when copying from a source dimension with month-level granularity to a target dimension with day-level granularity.
If a source dimension month starts on January 1st, 2027, this month will be mapped to the day member January 1, 2027 on the target dimension. This pattern will be repeated for all dimension members.
As part of the 2025 Forecast Income Statement for ABC Corporation, Jen must calculate the labor and benefits. She'll first copy then labor hours from HR and then calculate the labor and benefits.
You are a member of the planning team at ABC Corporation and you are responsible for creating and configuring data actions. Before Jen can calculate labor values in the expense model, you need to create a data action to copy the labor hours from the HR model into the expense model.
To do this, you need to create a cross-model copy data action.
In this practice exercise, you will:
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