Building Stories

After completing this lesson, you will be able to:

After completing this lesson, you will be able to:

  • Create a simple story

Story Design Concepts

What Is a Story?

Stories are at the center of the SAP Analytics Cloud experience. They are presentation-style documents that use charts, visualizations, text, images, and shapes to describe data.

A story is where you explore data interactively to find insights, visualize information with charts and tables, and share, present, and comment on your findings with colleagues. Before you get started, it is helpful to know a few basic things.

Stories have two main views.

What Are Dimensions and Measures?

Whichever view of a story you are using, the key to the underlying data lies in the measures and dimensions defined in the model of your data. Measures represent quantities that provide meaning to your data, for example, sales revenue, salary, or number of employees. Dimensions represent categories that provide perspective on your data, for example, product category, date, or location.

Dimensions can contain attributes that further describe a dimension. For example, you may have a dimension for customer which has attributes such as phone number and address to further describe the customer dimension.

Together, the dimensions and measures are the framework for viewing data in interesting ways, whether it be a trend line of revenue over time, or a comparison of gross margin across different regions.

How to Start a Story

Watch this video to learn how to start a story.


There are also specific object functions, such as pinning a chart on the Home screen. To access specific object functions, choose the More Actions icon on the widget (table, chart, and so on).

Formatting Options

You can find all story formatting options in the Styling panel in Edit mode. The formatting options available depend on the components of the story.

Guidelines for Data Visualization

There is no right or wrong way to tell a story; that is entirely up to you.

The figure Visualizations lists some options for data visualizations.

A section allows users to scroll through reports by member; for example, scroll through a report of customers by division.

There are, however, general design principles that can help you create meaningful, attractive stories that provide useful information.

Follow some simple guidelines to create your own visualizations.

Story Pages

When creating SAP Analytics Cloud stories, keep the following in mind:

  • SAP Analytics Cloud stories have one or more pages.
  • Each page has one or more charts/tables.
  • Each chart or table has one or more datasources.
  • A datasource can be an SAC Model or Dataset.
  • A datasource is based on either data in SAC or data in a source system accessed via a connection.
  • When creating a story based on a file, a story-specific data source is created.
  • A chart/table will normally use only one data source. In some cases however, blending two or more data source into one chart/table may be needed.

Page Types

A story page can be a blank canvas, a responsive page, or a grid.

You can add multiple pages to your story to help you explore and present your data. From within a story, use the +Add New Page option. This option is visible when you hover near the page title.

If you select Examine in a story, you get a grid for the chart you are looking at.

Drag and Drop Story Creation

Drag-and-Drop Story Creation

You can create either type of dataset with simple drag-and-drop on the Home page. Watch this video to learn how.

Create Stories with Explorer

Business Example

You have a file that contains SAP Concur travel data and you want to use the SAC explorer functionality to automatically create visualizations for your story on the fly.

Task Flow

In this exercise, you will perform the following steps:

  • Use drag & drop to create a story
  • Create visualizations with the explorer feature
  • Add the visualizations to the story
  • Add a grouping dimension

Creating Stories from Datasets

A dataset is a simple collection of data, usually presented in a table. You can use a dataset as the basis for your story, and as a data source for Smart Predict. Datasets complement models. Datasets are more suitable for ad-hoc analysis, while models are more suitable for governed, controlled use cases.

SAP Analytics Cloud has two types of datasets:

  • Embedded - Embedded datasets are embedded into a story and are unique to that story. They cannot be shared outside the story or refreshed.
  • Public - Public datasets are stand-alone datasets and can be shared among different stories.

Both types of datasets can be enhanced with basic data transformation/wrangling functionality. While neither dataset can be scheduled for a refresh, you can manually re-import updated data, and any transformations you have made remain intact.

Both datasets can be secured to allow users access to the dataset or not. Specific column-based or property security, however, is not supported for any datasets.

You can convert an embedded dataset to a public dataset. However, a limitation to a public dataset is that you cannot change its data source. For example, if your public dataset was originally created from a flat file but you now want to use a BW query, you have no option to make that change. Embedded datasets, on the other hand, do allow you to change the data source via the "Add New Data" option.

You can also convert an embedded dataset into a model, but any transformations you made to the dataset are lost and must be recreated in the model.

A public dataset cannot be converted to a model.

Datasets vs. Models

Here is a summary of the differences between datasets and models.

For simple, quick, ad-hoc data analysisFor formal, governed data analysis
Supports more cells/columns than modelsLimited to 100 columns
Can access live data only from on-premise HANACan access many live data sources
Does not support Planning use casesSupported for Planning use cases

Overall, in SAP Analytics Cloud, datasets and models complement each other. Datasets are perfect for ad-hoc, ungoverned use cases based on acquired data. Models are used when the use case requires more governed data analysis and planning scenarios.

Simple Filters

Story and Page Filters

Use story and page filters to narrow the scope of your analysis.

Story filters allow you to apply filters for all charts in a story that are based on the same model. They are used for specific dimensions or measures and can apply to all components of a story.

Page filters are the same as story filters, but apply to only one page in a story.


Page and story filters are enabled only after you have added at least one data source to your story.


A data source for a chart or table may prompt you to select members before data can be displayed. If the data source you select to create a chart or table has prompts or variables to be set, a prompt will appear when you create the first chart or table that uses the data source. After the responses to the prompts/variables are set, the information you provide will be used by all tables and charts that use the same data source.

Create a Story Based on a File

Business Example

You need to analyze some new sales data that is contained a file. You may need to perform some transformations on the data and you also want the system to automatically generate visualizations that you may adapt and use in your story.

Task Flow

In this exercise, you will perform the following tasks:

  • Create a story based on a file (SALES2022ACTUAL_EUR.csv)
  • Evaluate the raw data in the dataset
  • Perform some data transformations (wrangling)
  • Create a chart in a responsive page
  • Re-visit the data and create another chart
  • Create a canvas page and format it
  • Create a grid page and add a table
  • Save the story
  • Use both Edit and View mode

Save progress to your learning plan by logging in or creating an account