SAP Analytics Cloud
What is SAP Business Data Cloud?
In this lesson, we introduce you to SAP Business Data Cloud. SAP Business Data Cloud is a Software-as-a-Service
solution equipped with data and analytics services. With SAP Business Technology Platform providing foundational
services, SAP Business Data Cloud combines strategic solutions such as SAP HANA Cloud, SAP Datasphere, and SAP
Analytics Cloud and their respective capabilities into one single solution.
This lesson is temporarily included in all SAP Analytics Cloud learning journeys, so if you have previously completed
the Introducing Business Data Cloud learning journey or have seen this lesson in another SAP Analytics Cloud
learning journey, please continue to the next lesson.
0.1The Advantages of SAP Business Data Cloud
In this lesson, you'll discover the main advantages provided by SAP Business Data Cloud and its key
innovations that meet the challenges of organizations that want to make data-driven decisions.
Organizations that make data-driven decisions today face three big challenges:
1. Uncover the hidden potential in their business by unlocking seamless access to critical insights.
2. Boost confidence in their data quality and integrity to empower data-driven decisions.
3. Harness the power of fragmented, unstructured data sources and turn them into valuable business insights.
SAP Business Data Cloud was built to address these key challenges.
SAP centralizes data from SAP and non-SAP sources into a unified semantic layer, unlocking a new dimension of
insights, advanced analytics, and AI capabilities. By integrating cross-company data, businesses gain actionable
intelligence to bridge transactional processes and drive AI-powered growth. SAP’s AI agents leverage accurate,
context-rich data from both SAP and non-SAP systems to deliver advanced automation, seamless cross-solution
collaboration, and innovative decision-making, enabling businesses to adapt, innovate, and thrive at scale. Every part
of the business is deeply connected, driving today’s digital first world.
SAP Analytics Cloud
Let's introduce the core innovations of SAP Business Data Cloud that drive these changes.
One solution for all data and analytics requirements
SAP Business Data Cloud is a Software-as-a-Service solution equipped with data and analytics services needed in a
modern world. Together with SAP Business Technology Platform providing foundational services, SAP Business Data
Cloud combines strategic solutions such as SAP HANA Cloud, SAP Datasphere, and SAP Analytics Cloud and their
capabilities in one single solution.
Single solution for diverse audiences and use cases
What makes SAP Business Data Cloud so powerful, is that it offers the tools and technologies to meet all data and
analytics requirements of a modern and agile organization. It uses the latest technology to support scenarios such
as:
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Out-of-the-box reporting.
Machine learning and artificial intelligence.
Advanced data modeling and data warehousing.
Powerful planning and reporting.
Intelligent data management.
SAP Business Data Cloud provides data warehousing features including a manual data integration and data modeling
approach, AI and machine learning based extensions of data models as well as innovative out-of-the-box reporting
capabilities side-by-side. With this wide range of functions, it covers all the requirements of a modern data and
analytics solution and thus serves different target audiences with different requirements.
SAP Analytics Cloud
Unit 1 Navigating in SAP Analytics
1.1 Introduction to SAP Analytics Cloud
SAP Analytics Cloud is an end-to-end cloud solution that brings together business intelligence, augmented analytics,
predictive analytics, and enterprise planning in a single system. As a cloud-based system, you can perform all these
tasks from anywhere, on any device. SAP Analytics Cloud provides the analytics foundation for the SAP's Business
Technology Platform.
1.2 SAP Analytics Cloud Core Functions
 Business Intelligence (BI)
Empower business users to safely and securely work with governed data and create interactive stories and
dashboards. Uncover and deliver actionable insights across the enterprise with intuitive self-service analytics.
 Augmented Analytics
Automatically receive strategic insights with SAP Analytics Cloud's embedded artificial intelligence (AI) and machine
learning (ML) technology, allowing you to go from insight to action in a fraction of the time. Avoid agenda-driven
decision making by unveiling the true story of what is driving your business.
 Enterprise Planning
Make end-to-end decisions with confidence in one single workflow, from planning to insights. Drive better business
outcomes and gain full alignment across all business areas with extended planning and analysis in SAP Analytics
Cloud.
 Enterprise Platform Services
Gain a holistic view of your business in seconds with a seamless blending of multiple data sources. Live connections
to both cloud and on-premise data sources eliminate silos and streamline secured access to information. This
enables end-to-end analytics for the intelligent enterprise.
1.3 Using SAP Analytics Cloud Terminology
While there are many terms unique to SAP Analytics Cloud, here are a few that you will encounter regularly, both in
this course and in your day-to-day activities with SAP Analytics Cloud.
 Canvas page
A canvas page is a blank canvas allowing you to add any story elements anywhere on the page. The page is a fixed
height and width, no matter what device, or size of device, is being used to view the story.
 Connection
A connection is fundamental to communicating between SAP Analytics Cloud and a specific data source. System
administrators create connections to the specific data sources for your stories and analytic applications.
 Data Analyzer
Data analyzer is a predefined ready-to-run application for Live SAP BW queries, Live SAP HANA views, SAP
Datasphere models, and SAP Analytics Cloud models for ad-hoc analysis. Data analyzer is limited to a tabular view or
very basic charts of the data, but there is a filter area and a builder panel with navigation capabilities to add and
remove dimensions and measures to and from the table and create calculated measures. In addition, a menu bar
gives you a Refresh option and an Edit Prompts dialog, in case your data source is designed for setting prompts.
SAP Analytics Cloud
 Digital Boardroom
Digital Boardroom is a place to design an interactive boardroom presentation with access to real-time data, allowing
you to make fact-based decisions to drive your business. In addition to exploring directly on live data to discover
relationships and drill into details, you can plan and simulate the effects of different assumptions and actions visually
using value-driver trees.
 Model
A model is a representation of specific business data of an organization or business segment. A model is the basis for
stories and analytic applications.
 Planning
Planning in general is all about setting strategic goals and then determining how to meet those goals by creating
budgets, tracking progress in forecasts, and simulating scenarios to find new opportunities. Planning functionality
within SAP Analytics Cloud enables you to perform all these activities in one simple interface.
 Responsive page
A responsive page is a story page that will adjust the size and location of the elements on the page depending on the
device, or size of device, being used to view the story.
 Story
A story lets you explore data interactively to find insights, visualize information with charts and tables, and share,
present, and comment on your findings with colleagues. It can be either dynamic, with many interactive elements, or
very static, with little to no interaction capabilities.
 Widget
Widget is a generic term that refers to any element added to a story or analytic application. A chart or table is a
widget, as is a text box or image. There are many widgets available to add to stories.
Unit 2 Establishing Data Sources and Connections
2.1 Explaining Data Sources and Connections
 Data Connection Options
Connections provide the communication between SAP Analytics Cloud and your data sources. Those data sources
can be cloud-based or on-premise.
A connection must be made to a specific data source, so if you have more than one data source, you will have more
than one connection in SAP Analytics Cloud.
There are two types of connections – live and import.
 Live Connections
Currently, only SAP data sources/systems can be accessed using a live connection. In live connect data is not stored
in SAP Analytic Cloud and access to data is controlled by the source system
 Import Connections
Import connections can connect to many data sources/systems, even non-SAP such as Google Drive, SQL databases,
OData Services, and more. In case of import connections data is stored in SAP Analytic Cloud and any changes made
in source system will not be impacted in SAC until re-imported
SAP Analytics Cloud
Additional Information
Your organization must decide which connection type to use, according to your own unique needs. As you evaluate
which connection type to use, consider the following criteria:
 Functional needs
 Data privacy constraints
 Data volume constraints
It is also important to review the system requirements and technical prerequisites, and to check whether your
landscape is compliant with what is supported for your version and connection type.
For more information, see: The SAP Analytics Cloud System Requirements and Technical Prerequisites
If you are an administrator who wants to further explore live and import connections, go to: Creating Data
Connections for Cloud Applications in SAP Analytics Cloud and Creating Data Connections for On-Premise Data
Sources in SAP Analytics Cloud
2.2 Creating Insights Using Data Analyzer
Data analyzer is a predefined ready-to-run service for SAP Business Warehouse (SAP BW) queries, SAP HANA live
views, SAP Datasphere models, and SAP Analytics Cloud models for ad hoc analysis.
All SAP BW queries, SAP HANA live views, and SAP Datasphere models can be accessed directly in the Select Data
Source dialog, and no additional model is created.
 Data Analyzer User Interface
Data Analyzer provides either a tabular or chart view of your data, a filter area, and a builder panel with drag-anddrop capabilities to add and remove dimensions and measures from the table. In addition, you have a menu bar with
a Refresh option and an Edit Prompts dialog (if your data source is designed for setting prompts). Finally, you can
SAP Analytics Cloud
create calculated measures to enhance your analysis. These calculations exist only in the insight and are not
transferred to the data source.
After you have drilled down to the data details according to your needs and analyzed your data, you might want to
save this insight. For this, choose Save in the upper left corner of Data Analyzer. In the Save Insight dialog, select the
file location for your insight and enter a name and description for it.
 Create a Data Analyzer Insight
Business Scenario
You have been asked by your team to create an insight accessing data from SAP HANA without performing a data
import.
Task Flow
In this practice exercise, you will:
 Create a new insight from an SAP HANA data source
 Add conditional formatting to the insight
 Add a calculated measure to the insight
Unit 3 Using Modeling
3.1Explaining Modeling Options
 Dimensions
Dimensions represent categories that provide perspective on your numeric data; for example, product category,
date, region, cost center, and so on. Dimensions can contain properties that further describe a dimension. For
example, you may have a dimension for customer which has properties such as phone number and address to
further describe the customer dimension.
Dimensions can also be rolled up into a hierarchical view; for example, time (year, quarter, month), geography
(country, region, location), employee structure (executive, manager, employee), and so on.
 Measures
Measures represent the numeric values that you are analyzing; for example, sales revenue, salary, number of
employees, quantity sold, and so on. Sometimes these quantities are contained in a single dimension referred to as
an Account type dimension (and probably with the name Account, or something similar). In this situation, the
numeric values represent the line items on a corporate balance sheet, income statement, profit/loss statement, and
so on. But you can also present the numeric values as individual elements called Measures.
SAP Analytics Cloud
Together, dimensions and measures are the framework for viewing data, whether it be a trend line of revenue over
time or a tabular comparison of gross margin across different regions.
 Models
Models are comprised of dimensions and measures and represent a specific subset of data; for example, sales,
production, financial, shipping, etc.
Models are the primary data sources for SAP Analytics Cloud stories.
In SAP Analytics Cloud there are two styles of models:
o
o
Analytic model: read-only
Planning model: read/write
We will look at each style in more detail in the next concepts.
 The Modeler
The
Modeler area of SAP Analytics Cloud is where you create models. According to your data integration
strategy, you can create a new model one of 2 ways:
o
o
Create a model
Create a live data model
 Analytic Models
An analytic model is used strictly for read-only data reporting and analysis. A date dimension is available but is not
required, and you can remove it from the model during the design stage.
Why is a date dimension optional? One scenario is that the model represents only current data. Because users know
the data is always "current," there is no need for a date dimension.
SAP Analytics Cloud
 Planning Models
Planning models are pre-configured with required dimensions for Date and Version. These dimensions are required
because planning activities are dictated by time frames, and the planning numbers are intended for different
purposes – budget, forecast, and planning. Planning models offer support for security features at both the model
level and dimension level.
When working with a planning model in a story, users with planning permissions can create their own versions of
model data. These users can also write data to the model by typing new values, copying and pasting data, and using
data actions.
SAP Analytics Cloud
 Datasets
A dataset is a simple collection of data usually presented in a tabular format. You can use a dataset as the basis for a
story.
Types of Datasets
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 standalone datasets and can be shared among different stories.
Both types of datasets can be enhanced with basic data preparation and transformation functionality.
Neither dataset can be scheduled for a refresh; you must manually re-import the updated data. SAP Analytics Cloud
automatically matches the columns of the newly acquired data to the columns of the existing data, but any prior
data transformations will be lost.
If you import data from a flat file, you can only re-import a compatible file: a file that has the same number of
columns as the original file, and with the same column names and data types as in the original file.
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.
Converting 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 an SAP Business Warehouse 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, however, cannot be converted to a model.
SAP Analytics Cloud
Compare Datasets and Models
Overall, 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.
3.2 Exploring Model Data Sources
 Live Data
We have already discussed live versus import connections. Models use those connections to reflect specific data
from that data source. A live model simply uses a live connection for the data it represents.
Since a live connection merely provides access to data, there is no data contained in a SAP Analytics Cloud live
model. The model only points to the specific data in the live data source.In addition, you cannot write data to the
model (because doing so would really be writing back to the original source system), so live models are analytic
models. The single exception is a live model to SAP BPC Embedded, but that is outside the scope of this course.
Because only SAP sources can be accessed using a live connection, a live model reflects only SAP data.
 Create a Live Model
The process of creating a live model to any SAP source is very simple as you can see from the summary of steps
below. We will create a live model in the practice exercise in the next lesson.
1. From the Navigation Bar choose
Modeler.
2. Select Live Data Model.
3. Choose the appropriate System Type, Connection, and Data Source in the Create Model from Live Data
Connection dialog box. Remember, the Connection and Data Source are unique to your organisation
SAP Analytics Cloud
4. View the measures and dimensions.
5. Save the model.
Acquired Data
An import model uses an import connection to import (copy) data from a source database or system into the SAP
Analytics Cloud model. This means that there are always two versions of the data – one version in the original data
source and the copy in SAP Analytics Cloud.
Because the data is copied into the model, if the original data source changes, the changes are NOT reflected in the
model. As it is very likely that data in the original data source changes regularly, you can schedule the import process
to occur on a regular basis in order to keep the model data in sync with the original data source.
Schedule Data Import:
In addition to being able to schedule the data import process, you can also manipulate the data in the SAP Analytics
Cloud model. It is a copy, so none of the manipulations are reflected in the original data source. The data
preparation interface is user-friendly and fairly intuitive.
SAP Analytics Cloud
Modeling Work Flow
Regardless of the style of model (analytic versus planning) or type of model (live versus import), the overall modeling
work flow is the same.
1. Identify your data sources
2. Decide to acquire data, use live data, or both. Things to consider in this decision include:
 Performance
 Security
 Planning
 Smart Predict
 Necessary data wrangling
3. Create connections in SAP Analytics Cloud
4. For live data, create live models
5. For imported data
 Create dimensions and import mast data
 Create models and import transaction data
6. Create stories
3.3 Creating a Basic Model
Create a Live Model
 Business Scenario
Your team has asked you to create a live model as they need to access real-time data from your SAP HANA onpremise system for simple data analysis.
 Task Flow
In this practice exercise, you will do the following:
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Create a live data model in SAP Analytics Cloud
Connect to an SAP HANA on premise system and select a calculation view
Select order date as the time dimension
View the data in data analyzer
Additional Learning
For more information on modeling, the topics in this unit are covered in more detail in the Designing Data Models
and Transforming Data in SAP Analytics Cloud learning journey.
Unit 4 Using Basic and Advanced Stories
4.1 Viewing and Interacting with a Story
 SAP Analytics Cloud Stories
An SAP Analytics Cloud story is the primary data reporting and analysis medium. It is often referred to as a report or
a dashboard because it can consist of detailed tables, highly visual charts, interactive elements, or a combination of
these options.
SAP Analytics Cloud
The following figure shows different views of an SAP Analytics Cloud story, a dashboard of summary information and
a more detailed view of the data.
 Working Modes
All SAP Analytics Cloud stories have three working modes: View, Edit, and Presentation.
1. View Mode
When you open a story, you default to View mode. In this mode, you have very limited functionality and cannot
change the story other than with any interactive elements designed in the story. It is similar to read-only in other
applications
SAP Analytics Cloud
2. Edit Mode
In Edit mode, you have full control over the design of the story. You can add elements to the story, including new
pages. You can rearrange elements in the story. You can change or add interactivity to the story, and more.
3. Presentation Mode
In Presentation mode, you can create flexible and fluid presentations using the presentation viewer.
Objects used for this retain their interactivity and functionality. They replace static presentations and information
with interactive elements based on real data, allowing fact-based decisions to be made.
Presentation mode allows you to answer questions through direct analysis of current data, planning visually, and
simulating the effects of various assumptions and actions.
No separate license is required for the use of Presentation mode.
 Bookmarks
You can create bookmarks to save different states of a story.
When viewing a story, you may want to come back to the same view of the data every time, or you may want to set
up different states or scenarios. For example, you have several pages in your story that have filters or prompts
SAP Analytics Cloud
applied to them. You do not want to spend time resetting all of them each time you want to see a different scenario.
You would like to open the story, see one scenario, and then quickly switch to another scenario.
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Bookmarks can be either private or global. You can always save a private bookmark, but you need
appropriate authorization to save a global bookmark.
Bookmarks only include filters and prompts.
Bookmarks can be shared.
Note
When you create a bookmark, you can choose Customize Link in order to provide a meaningful label at the end of
the URL.
a. Add a Bookmark
Business Scenario: You are working with stories in SAP Analytics Cloud and you want to be able to quickly access
your story from your home page as well as bookmark specific story views and set them as the default view for a
story.
Task Flow: In this practice exercise, you will perform the following tasks:
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Pin a story to your Home page
Add bookmark of a story state and make it the default view for the story
View a story bookmark
 Export a Story
In either View or Edit mode of a story, you can export the entire story to either a .pdf, .pptx, or Google Slides file
type from the File menu.
SAP Analytics Cloud
Note that from the File menu, there is no option to export to .csv, .xls, or .xlsx file types. The export process is strictly
a presentation format.
There are options for exporting the story's data in other areas of the story elements. We will note some of these
options in the More Actions Button concept below.
 More Actions Button
a. More Options
In many areas of SAP Analytics Cloud, you have More options than can be displayed in the interface.
In some situations, seeing a More option depends on your screen size and resolution as well as your browser's zoom
setting. In other words, if you have a large monitor, your browser window may be large enough to display all the
possible options you have.
SAP Analytics Cloud
b. More Actions
While viewing and editing a story, however, there is a More Actions button available for every element of a story
(charts, tables, filtering devices, text, images, and so on). This option provides you with many more design- and
object-related options than the story can practically display.
You can think of the More Actions button as being similar to a context or quick menu you access by right-clicking an
object.
There will be different More Actions options depending on whether you are in Edit or View mode. When viewing a
story, there are fewer options.
In the following example, you can see some of the different options available when choosing More Actions when
editing a chart (left) or table (right).
SAP Analytics Cloud
Included in the More Actions button for charts, tables, and other data-dependent story elements is the option to
export data to a .csv or .xlsx file. Unlike the export option for the entire story, which exports only to .pdf, .pptx, or
Google Slides files, the More Actions export option exports the data reflected in the object.
SAP Analytics Cloud
 Export to Excel and PDF
Business Scenario: You are new to SAP Analytics Cloud and you need to learn how to use the export functionality.
Task Flow: In this practice exercise, you will:
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Export data from a data table to Excel
Export a story to a PDF document
4.2 Building Simple Stories
 Story Design
1. Story Page Types
When creating SAP Analytics Cloud stories, you have different page types from which to choose:
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Responsive: Required for viewing on mobile devices; dynamically changes layout depending on the viewer's
monitor/screen size.
Canvas: A fixed page size that does not change, no matter the size of the viewer's monitor size.
Grid: A table-only page that is available only in the Classic Design Experience and will not be available in the
Optimized Design Experience.
SAP Analytics Cloud
2. Classic Design and Optimized Design
When you create a story, you are prompted to choose Classic Design Experience or Optimized Design
Experience mode:
SAP encourages you to use Optimized Design Experience mode. The Optimized Design Experience includes many
usability and performance improvements and is the prerequisite for future story enhancements. There are a set of
features that may not be available at this time as SAP continues to enhance the Optimized Design Experience mode;
however, these and other new features are being added with each quarterly release and will be made available only
in the Optimized Story Experience. Furthermore, it will be the new default experience in future releases.
The Classic Design Experience is still be available but will be phased out. It provides access to features developed
prior to Q2 2022. However, it will not receive any performance, functionality, or usability enhancements.
Note:
For the most current information on what features are available with each design experience mode, always refer to
the SAP Help Portal in your current SAP Analytics Cloud tenant.
3. Guidelines for Data Visualization
There is no right or wrong way to tell a story; that is entirely up to you.
There are, however, general design principles that can help you create meaningful, attractive stories that provide
useful information.
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Choose direction: Define the importance of your visualizations.
Keep it simple: Ensure a user-friendly experience for viewers.
Follow general reading direction: Follow either left-to-right or right-to-left as appropriate for the audience.
Group information logically: Locate similar topics adjacent to each other.
4. Data Sources for a Story
Once you have a blank page in your story, you will want to add widgets to visualize the data in your story. The
simplest option is to choose either a chart or a table to add to your page. Select either option from the story menu
bar: Chart
or Table
(or, depending on your screen resolution, you may need to select the … More option in
the menu bar and select from there).
SAP Analytics Cloud
With either choice, you will be prompted to choose a data source, either a dataset or model to browse to and select
or a SAP Datasphere model. You will probably choose a model most often.
5. Left Side Panel
When creating a story, users have the option to use the horizontal menu options at the top of the screen or the Left
Side Panel. The panel can be toggled on and off from the Left Side Panel button in the View menu option.
At the top of the Left Side Panel users can select three different options:
1. Assets: All elements available in the horizontal menu can also be added to the story from the left side panel.
2. Outline: Access story settings, pages, and scripting.
3. Filters: View and apply story filters.
When elements are added from the horizontal menu, SAP Analytics Cloud positions them on the screen. With
the Left Side Panel, users can position the widgets or other elements in the exact position they require as displayed
in the following example.
SAP Analytics Cloud
6. Builder and Styling Panels
 Build Your Chart or Table
Next, you will build your chart or table. You may need to toggle the Right Side Panel button in
the View area of the ribbon to access the
Builder panel.
When you are in the Builder panel, you simply add the appropriate data to the various elements of the
widget.
The Builder panel, however, is only half of the entire panel. The other half is the Styling panel, which
provides many formatting options for every component of the story, including the page itself.
SAP Analytics Cloud
Build a Simple Story
Business Scenario: You need to access real time data from your SAP HANA on premise system for simple
data analysis.
Task Flow: In this practice exercise, you will do the following:
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4.3
Create a story with a responsive page
Customize your story
Working with Microsoft Add-ins
 Microsoft Office Integration with SAP Analytics Cloud
Rather than using SAP Analytics Cloud stories for data analysis, planning, and presentation, you can use SAP add-ins
to Microsoft Office.
The SAP Analytics Cloud, add-in for Microsoft PowerPoint allows you to you to embed SAP Analytics Cloud widgets in
your PowerPoint presentation.
The SAP Analytics Cloud, add-In for Microsoft Excel and SAP Analysis for Microsoft Office enable you to use Excel to
format, analyze, and enrich your SAP Analytics Cloud data.
SAP Analytics Cloud
You can insert one or several models in a workbook. Then you can add or remove dimensions and measures to
analyze your data. You can also add totals in rows and columns to your table. In your analysis, you can use
dimensions with hierarchies applied. You can expand and collapse the hierarchy nodes within the table.
There are also several formula functions provided that can be used for filtering, reading meta data, and creating cellbased reports. For example, SAP. GETDATA returns the data value for a specified set of dimension and member
combinations.
Finally, both add-ins accommodate planning capabilities, such as:
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Write-back
Revert
Publish
View changed cells with automatic highlighting
Add filters, subtotals, navigation attributes, properties
You can download all of the add-ins from the Microsoft Office store.
 SAP Analytics Cloud, Add-In for Microsoft Excel With SAP Analytics Cloud, add-in for Microsoft Excel, you
can bring your SAP Analytics Cloud data into Microsoft Excel and continue your analysis there. In this
example, you can see the additional SAP Analytics Cloud tab displayed in the Microsoft Excel ribbon as well
as sample formula functions available.
Additional Learning: SAP Analytics Cloud, add-In for Microsoft Excel is covered in more detail in the Creating
and Working with Microsoft Excel Workbooks Using the SAP Analytics Cloud, Add-in for Microsoft Excel
learning journey.
 SAP Analysis for Microsoft Office
SAP Analysis for Microsoft Office, commonly referred to as Analysis for Office, is a Microsoft Office add-in that allows
multidimensional analysis of SAP data sources, including SAP Analytics Cloud. It consists of the following plug-ins:


Analysis
Enterprise Performance Management (EPM)
SAP Analytics Cloud
Note:
While SAP Analysis for Microsoft Office can also be used to plan on SAP Analytics Cloud data, all future development
regarding SAP Analytics Cloud will be on the SAP Analytics Cloud, add-in for Microsoft Excel.
 SAP Analytics Cloud, Add-in for Microsoft PowerPoint
SAP Analytics Cloud, add-in for Microsoft PowerPoint is web-based and available with both PowerPoint for Web on
Windows and Mac.
Once you connect to your SAP Analytics Cloud tenant and have added a widget to your PowerPoint slide, you can
refresh the widget's data at any time. There is no need to go back to SAP Analytics Cloud to copy the information and
paste it into your slide each time there is an update to the data.
Using the add-in, you can easily find SAP Analytics Cloud stories and associated widgets, filter widget data as
required, and add widgets to your PowerPoint slide.
SAP Analytics Cloud
SAP Analytics Cloud, add-in for Microsoft PowerPoint with the add-in tab in the ribbon highlighted at the top of the
screen and the SAP Analytics Cloud panel open on the right (also highlighted).
Note
An SAP Analytics Cloud license is required to access data with the SAP Analytics Cloud, add-in for Microsoft
PowerPoint
4.4 Scripting Advanced Stories
 Advanced Scripted Stories
While you can use SAP Analytics Cloud story design capabilities for the majority of your reporting, dashboard, and
planning needs, you may need to work with developers in your IT organization to create more custom stories.
Stories can incorporate scripting so that developers can create a highly customized and interactive experience for
story viewers. However, a story can also be scripted to have even less functionality than a standard SAP Analytics
Cloud story, for example, removing all context menu options.
The broad range of customization options (from very static to highly interactive) possible through scripting options
when editing a story.
SAP Analytics Cloud
 Scripting Capabilities
The scripting language used for stories is a subset of JavaScript. The JavaScript Script Editor in the scripting
environment is similar to other SAP editors. You can use Ctrl+Space to access available functions and data to speed
up your script writing. In addition, the editor provides auto-complete and syntax check as you write.
 Extension Capabilities
Story design options are not limited to the defined set within the story builder. You can ask developers to create
custom widgets and R widgets to add even more visualization options to your stories.
SAP Analytics Cloud
Additional Information
Creating extended stories is covered in more detail in the Acquiring Basic Scripting Skills to Extend Stories in SAP
Analytics Cloud learning journey.
Creating R visualizations is covered more detail in the Create R Visualizations in SAP Analytics Cloud | SAP
Learning learning journey.
Unit 5 Using planning
5.1 Describing Planning Features
Planning is all about setting strategic goals for a business and then determining how to meet those goals by creating
annual budgets, tracking progress in forecasts, and simulating scenarios to find new opportunities. These plans are
formed by projecting historical data (known as Actuals) into the future, by gathering input from different
departments, and by considering trends, risks, and opportunities in the market.
Because planning activities are a collaborative effort, SAP Analytics Cloud provides many options and utilities to
make the entire planning process run smoothly. Let's take a look at how SAP Analytics Cloud can help with enterprise
planning activities.
 Planning Features
SAP Analytics Cloud has many planning features that help you plan simpler and faster. These features are covered in
detail in the Leveraging SAP Analytics Cloud Functionality for Enterprise Planning learning journey. Below, we will
provide an overview of the following:
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Data entry
Version management
Data locking
Data actions
Validation rules
Validation driver trees
Structured allocations
In addition, SAP Analytics Cloud can be integrated with on-premise SAP planning systems, allowing you to maintain
your investment in an existing planning system and use SAP Analytics Cloud as the front-end for planning activities.
Let's go through each planning feature in more detail.
 Data Entry
Data entry is based around the table, where you can type relative or absolute values into individual cells. You can
copy cell values, along with all the data that aggregates up to the copied value. You can plan at any level of a
hierarchy, and the data will automatically be rolled down to the lowest level.
When then data changes, the affected cells are shaded yellow, indicating the data entry function is being used but
not saved. Data entries can be tested before you save and publish them.
You can type an absolute value in a cell, or type a relative value such as *2 or +500 to perform simple mathematical
calculations on existing data. For example, if the data value in a cell is 100, and you type *2 in the cell, the value will
change to 200.
SAP Analytics Cloud
 Version Management
When you are planning for all possibilities, it helps to understand how different plans relate to each other and to
your actuals data. Version management helps you to complete tasks such as the following:
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Carry out variance analysis, such as making sure that your working forecast is on budget.
Quickly explore, share, and publish different scenarios without losing sight of the original data or introducing
unnecessary complexity.
Work on your own data until you are ready to publish.
Try a change and undo/redo.
Use the history to see what happened with the data.
Roll a private version back to a previous state if you need to take a different direction.
Revert all changes to the original values.
 Data Locking
With data locking, you can choose sections of data to lock when you are getting ready to close your books. Each
section can also be delegated to owners who can lock the data themselves, or set the data to a restricted state
where only the owners can edit it. You can then schedule changes to data locks in the Calendar.
SAP Analytics Cloud
 Data Actions
With data actions, you can model sequences of copy-paste operations, allocation steps, and advanced formulas.
With advanced formulas, you model complex processes such as cash flow planning, depreciation, and carry-forward
operations. You can build these formulas using a visual editor that does not require scripting knowledge, although a
scripting engine is also available for fine-tuning.
Copy operations make it easy to move data from one part of a model to another, or to a different model. For
example, if you have separate models for Headcount and Expense Planning, you can use a data action to copy data
from those models into a central Finance model.
To make your data actions more flexible and easier to update, you can also add parameters that can be set while
designing or running the data action. You can also run other data actions as steps within your data action, letting you
quickly reuse common calculations.
Planning users can run data actions in a story. Alternatively, you can use the Calendar to schedule them to run
automatically.
SAP Analytics Cloud
SAP Analytics Cloud data actions are like planning functions and data manager packages in other SAP planning
solutions.
 Validation Rules
Validation rules let you define valid member combinations across dimensions to prevent improper data entry and
planning operations in stories based on a specific planning model. For the dimensions you define in a dimension
combination rule, only the member combinations that you specify as allowed combinations can pass validation.
For example, you might want to increase sales of certain products in specific locations. You create a validation rule
between the product dimension and location dimension members. Planning users can do planning only for the
allowed combinations of products and locations.
 Value Driver Trees
Value driver trees let you take a driver-based planning model and turn it into a streamlined visualization for running
simulations and making strategic decisions. For example, you might be discussing how vulnerable your business is to
raw material prices, or which product line to grow over the next few years to increase profitability the most. Value
driver trees allow you to book values to drivers and inputs, visualize the flow of value through the accounts, and see
the overall impact on KPIs now and in the future.
You create value driver trees directly in the story. The option to add nodes automatically based the model’s account
structure can help you get started quickly, but you can still add and customize nodes as needed. Features like undo
and redo, search, and drag-and-drop node linking make it easy to get set up.
SAP Analytics Cloud
 Structured Allocations
You can use structured allocations to establish reusable steps for allocating costs, such as allocating the cost of IT
support across different departments by support hours used, or the cost of travel across different product groups
based on cost-of-living rates for the customer location.
You build allocation steps using a visual tool that does not require scripting expertise, but that covers a range of
different allocation workflows.
Perform Manual Input Planning Tasks
Business Scenario: You have been asked to create an operating income forecast for your company.
Task Flow: In these practice exercises, you will:
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Create a story and configure the data table
Use simulation features
Work with private data and publish it
Lock cells
SAP Analytics Cloud
5.2 Simulating Data with SAP Analytics Compass
 What is SAP Analytics Cloud Compass?
Compass is a native SAP Analytics Cloud feature which enables the simulation of probable impact brought about by
driver uncertainties. It utilizes the relationship defined between the driver and target within the SAP Analytics Cloud
model. With compass, you are able to perform scenario modeling of different assumptions and compare the
probable outcomes.
Create simulations from a story table or the compass start page to answer business questions that you may have.
You are able to simulate uncertainties in key drivers and the impact probability right away without additional IT
setup or prior mathematical definitions.
 Compass Simulations and Time Series Forecast Predictions
It is important to remember that a compass simulation is not the same thing as a time series forecast prediction.
Time series forecasts project the data trend from historical values into the future. It is not reliant on existing
mathematical definition between the KPIs. You need to have enough historical data to detect the trend for the
desired period into the future. The kind of business questions leading to a time series prediction center around what
happens if things develop at more or less the same rate.
Time series forecasts provide answers when you want to know what will happen in the future if the current trend
persists. An example of a question you would ask when using a time series forecast prediction could be, What is the
predicted operating income if the trend for COGS development in the past 4 years persists?
SAP Analytics Cloud
SAP Analytics Cloud compass simulations use the Monte Carlo simulation, a mathematical simulation method
delivering a range of probable outcomes as result. It does not analyze data trends, but instead, relies on repeated
calculation using random inputs. This also means that a formula or definition of relation between the impacted KPI
and the drivers is required before the simulation can be executed. As this method explores possible outcomes
brought about by random inputs, the business questions leading to a compass simulation should center around what
happens if things change.
SAP Analytics Cloud compass provide answers when you what to know the probable impact if there are
uncertainties to driver performances. An example of a question you would ask when using a Monte Carlo simulation
could be, What are the probable results of operating income if the COGS is between 10 to 20 million dollars?
Some typical use cases for compass include understanding the risk context during target setting, budget reviews,
strategic or workforce planning, just to name a few. Basically, compass is not limited to any use case, as long as the
relationship between target and driver(s) are defined within the SAP Analytics Cloud model.
In summary:
Compass
Simulation
Time Series
Prediction
Does it require historical data to analyze trends?
No
Yes
Does it require defined mathematical relationship between
influencer/drivers and the target KPI?
Yes
No
Can you use time series forecasts and compass simulations together? Yes, you can use both to enhance the
attainable insights. For example, you could generate a time series forecast for an observation of what would happen
in the future if the current trend persists and then perform a compass simulation on top of the predicted version to
understand the risk context if a few key drivers are unexpectedly impacted.
Run a Compass Simulation
Business Scenario: You have been provided with information that may affect the forecast numbers for the year. You
learn that there will be an increase in the cost of raw materials and some churn in the EMEA region. You also know
that there is a possibility of a substantial increase in gross sales in the US due to potential deals.
You want to simulate the potential impact and using the range of uncertainties provided by your team. You create a
compass scenario to explore the impact of an increase in raw material cost, an expected churn in EMEA, and a
potential sales increase in the US.
SAP Analytics Cloud
Unit 6 Using Basic Augmented Analytics in SAP Analytics Cloud
6.1 SAP Analytics Cloud Augmented Analytics Functionality
SAP Analytics Cloud provides you with many artificial intelligence and machine learning utilities to assist you in your
data analysis and planning activities.
 Smart Predict
Create one or several predictive models that automatically learn from your historical data, and find the best
relationships or patterns of behavior to easily generate predictions for future events, values, and trends. For
example, predictive forecasting takes different values into account, and also looks at trends, cycles, and fluctuations
in your data. Smart Predict can be used on:
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Acquired data is supported for datasets and planning models but not for analytic models.
Live data is supported only for SAP HANA on-premise.
Note:
Smart Discovery and Smart Insight features are only available in classic design stories. They are not included in this
learning journey. For more information, visit the SAP Help Portal.
 Just Ask Feature
Request information in natural language simply by typing a question about your data using the SAP Analytics Cloud
just ask feature. You can access this AI-driven feature from the Home page or from the icon in the main horizontal
menu.
The SAP Analytics Cloud just ask feature supports a variety of different natural language query (NLQ) input options,
so simply ask your questions (using U.S. English) and instantly get answers displayed as either simple tables or charts.
For example, you can ask the just ask feature to show you data for:
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Sales by region
Sales for 2023
Sales for this quarter
Top 3 products by gross margin
SAP Analytics Cloud
in the following example, you can see a chart created using the SAP Analytics Cloud just ask feature and six of the
key points to note.
1. Open the just ask feature from your horizontal menu bar, as highlighted in the previous image.
2. Select your model using the Select model dropdown list, as shown above.
 Select Add Model to Search to add models to the current session.
 If a specific model you want to search is not listed, you can request to have it indexed for the just ask
feature by selecting Click here to create a model request to an admin.
3. To help you with starting a query, select the + Add to Search icon to the left of the search field. Select any
entry from the list available measures, and dimensions to populate the search field.
4. Enter your question directly in the field and press the Search icon. Depending on the target model, the actual
inputs will vary.
 As you type, you can select auto-complete suggestions to populate the search field.
 Keyword suggestions will display below the search field. Select any to add them to the search
question.
5. Interact with the data using the interaction options (from left to right):
 Change from a Chart to a Table using the first two interaction options.
 Select the Analyze Data icon to open the Data Analyzer in a separate tab, displaying the data from
your search result.
 Copy your charts by using the Copy icon to copy the card and paste the contents into a story page
using the Ctrl + V shortcut.
 Select the More Options option to set or reset drill levels, sort the display in ascending or descending
order, set rank, or export the data as CSV or Excel files.
6. The Suggestions section is a list of queries generated by the system to help you explore different aspects of
the current data model.
SAP Analytics Cloud
Additional Information
The SAP Analytics Cloud just ask feature must be enabled by system administrators. Currently, Search to Insight is
the default application. For more information on the SAP Analytics Cloud just ask feature, including the most
complete and up-to-date list of supported prompts and restrictions, you can visit Exploring Your Data with Just Ask |
SAP Help Portal
For more information on Search to Insight, you can visit Search to Insight | SAP Help Portal
Use the SAP Analytics Cloud Just Ask Feature to Analyze Data
The SAP Analytics Cloud just ask feature is a natural language query interface used to query data. Simply ask it a
question, and it will recommend a chart to insert into your story. It is a quick and easy way to explore your data.
Business Scenario: You are working in a team that must report on operating expenses for your company. You aren't
sure where to start, so decide to use the just ask feature in SAP Analytics Cloud.
Task Flow: In this practice exercise, you will:
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Access the just ask feature from the Home page
Create a search query
Refine the query to further explore data
SAP Analytics Cloud
Unit 7 Using Collaboration Features
7.1 Access and Contribute to Discussions
 Discussions
You can use the Discussion feature to easily collaborate with teams and users.
To create a discussion, select the
Collaboration icon. Choose one or more people with whom you wish to
collaborate, and then start a conversation. You can message, add attachments, and even link to other stories using
the plus icon at the bottom of the assistant.
 Add Comments
Commenting is a great way to offer feedback on specific elements in a story. Select the element on which you wish
to comment, choose the comment icon, and enter your message. Comments can be addressed to specific team
members by tagging them with the @ symbol.
Comments can be made on a story page, a widget, or a data point in a table. Your comments can be up to 10,000
characters long, excluding comments on dimensions (comments on dimension have a limit of 255 characters). They
can also be exported to a file from the story. SAP Analytics Cloud keeps track of the commenting history.
7.2 Using the SAP Analytics Cloud Calendar
 Calendar Tasks
Use the SAP Analytics Cloud calendar to organize your work flows. You can create different types of tasks and assign
people to work on them and others to review the work. You can use processes to manage multiple tasks.
SAP Analytics Cloud
The calendar provides following features to view, create, and manage your tasks:
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Collaborate
Set and track status
Assign reviewers
Add reminders
View due dates
 Scheduled Publications
You can also use the calendar to manage scheduled publications. When you have scheduled a story or application,
the scheduling job appears on your calendar. From the calendar you can view, modify, copy, discontinue, or delete a
schedule.
Note:
Users with the Manage permission on Schedule Publication can alter a schedule you have created.
Use the Calendar to Collaborate with Colleagues
Business Scenario: You are part of a team with multiple contributors to a story. You need to create a task to have an
edit that you have performed reviewed and approved so you use the SAP Analytics Cloud calendar to collaborate
with your colleague.
Task Flow: In these practice exercises, you will:
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Create a composite task in the calendar and define a reviewer
Send a message to your reviewer indicating you removed dimensions from the table
Review and approve the story as a reviewer
View your calendar task to see that it is completed