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Posted on July 19, 2018 under Analytics, Cloud, SAP for Beginners

By: Fernando Ibarra Avila
Sr. SAP Business Intelligence Associate


Introduction to SAP Analytics Cloud

SAP Analytics Cloud is one of the many tools in a new wave of products provided by SAP.  While many of our clients are still trying to figure out a use case for Leonardo and block chain technologies in their business, it goes without saying that SAP Analytics Cloud (SAC) seems like a straight forward path.  With more environments gradually moving toward the cloud, it makes sense to have the analytics platform, used by business users, be based on the cloud as well.

In this post, we will look at some of the features and capabilities of SAC including data source connectivity, development of a basic workflow, and provide some initial thoughts on the tool itself.


Data Source Connections

Analytics tools are only useful if they can connect to the data that the business wants. The last thing that any IT specialist wants to do is move data and data models around to accommodate front-end analytics tools. With SAP Analytics Cloud being hosted on the cloud, the challenge of connecting to on-premise data sources rises. Luckily, SAP provides plenty of documentation and “Guided Playlists” of how to configure your environments. As part of our series regarding SAP Analytics Cloud, we will create a runbook-style blog to guide anyone interested on how to set up a live connection to SAP HANA. 

However, as a quick summary, the steps are:

  1. We must go into the HANA system and add the appropriate user roles and privileges to users, configure the XS Server, change some parameters, and enable Cross-Origin Resource Sharing (CORS) support.
  2. Once configured in the HANA side, we need to create a live data connection in SAC.


All the connections that are created can be viewed in SAC by logging in and going to Menu > Connection. This is the same location where administrators create and manage connections to the various on-premise connections.  At a quick glance, it seems that SAC supports both Live connections and data extractions. As of July 2018, the extractions supported are the following:

SAC blog 1

The supported Live connections supported are the following:

SAC blog 2

It is important to note that the version of SAC that I am playing with is 2018.12.0.  Also, for reference, you should look at the SAP notes in the reference section of this document as a good starting point for connecting on-premise data sources to SAC.


Basic SAC Workflow

Once a connection to a source is established, data models need to be created.  The data models are the objects that will be consumed by visualizations to create content for dashboards and reports.  Users can create models by going to Menu > Create > Model.  This will lead users to the following page: 

 SAP Analytics Cloud (SAC), creating a model in SAC

The source of these data models can be csv files, SAP HANA views, or BW Queries. One thing to note is that when a user selects the ‘Use a datasource’ option, they will be prompted to use a live connection or extract data from one of the following environments:

 SAP Analytics Cloud (SAC), using a datasource in SAC

Once the appropriate source is selected, you will land on a page that looks like the following:

 SAP Analytics Cloud (SAC), using a dataset in SAC

One of the key concepts to point out is that SAC can determine the data quality of the data model itself.  For instance, notice the red values that are under the Order Date field in the dataset.  That means that there is an issue with the data quality.  Once I select that field, I can determine the issue is the data format that is used:

SAP Analytics Cloud (SAC), data quality in SAC

Once the date format is changed to MM/DD/YYYY the red outline is removed, as seen here:

SAP Analytics Cloud (SAC), fixing data quality in SAC

It is in this step that users and developers create calculated columns, hierarchies, and filters.  Once those procedures are complete, select the Create Model button at the bottom right to publish that model in SAC. 

With the new Data Model created, users will be able to use that data set for new Stories.  In order to create a Story, go to Menu > Create > Story.  The landing page should look like the following:

SAP Analytics Cloud (SAC), creating a story in SAC

As you can see, there are a couple of templates that can be used, but for our purposes we are going to create a simple Responsive Page

The canvas of SAC utilizes “Lanes”.  As far as functionality goes, it feels very similar to the functionality that you see from SAP Lumira Discovery.  There is a lot of Drag and Drop and right-clicking to see properties of each individual chart.  Overall the visualizations are quick to create.  It took me 5 seconds to create the one below:

 SAP Analytics Cloud (SAC), creating visualizations in SAC

From here, users can save their dashboard by selecting the File > Save option. 


Initial Thoughts on SAP Analytics Cloud

For anyone with experience with previous SAP tools, the transition to development and end user consumption in SAP Analytics Cloud will be simple. If anything, SAC will feel very much like SAP Lumira Discovery. The overall look and feel of SAC screams simplicity, which is what many end users want.  The sharing mechanisms for files in SAC work like SharePoint or any other cloud-based storage solution.  Most of the effort when creating reports and dashboards in SAC will come from the backend. Creating data source files (HANA Views, Queries etc.) that are appropriate for the needs of the business will simplify the amount of effort required to develop and maintain data models and dashboards.

Reference SAP notes:

  • 2358097 - SAP Analytics Cloud connecting to on-premise data *** Master KBA ***
  • 2589761 - Connecting to Live Data in SAP Analytics Cloud *** Master KBA ***


Does your team need SAC Training? If you're not sure, check out our Analytics Training Quickstart Guide to get all your questions answered.

Learn More


Jul 19, 2018 11:54:42 AM / by Fernando Ibarra Avila

Fernando Ibarra Avila

Written by Fernando Ibarra Avila

Fernando Ibarra Avila is a senior SAP BI Associate who focuses on developing and managing SAP applications. His areas of expertise include SAP HANA modeling, SAP Lumira, SAP BI/BW Reporting, BI Dashboards and modeling, Web Intelligence, and SAP BusinessObjects. Comerit has been lucky to have Fernando as a member of our Charlotte, North Carolina team since 2014.

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