Adding Value with SAP Analytics in the Cloud

In order to get the most value from analytics, you need a strong foundation.  Data volume and complexity are growing, which is causing a ripple effect into information visualization and analytics.  The cost to store data is decreasing, but not as fast as data volume is growing.  In addition, the complexity of the data is growing, which requires higher demands on performance to support enhanced relationships and business logic.

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SAP’s goals for analytics in the cloud are

  1. Simplify

  2. Experience

  3. Trust


Empower business users with ad-hoc and on-demand capabilities.  Rather than develop a complex and intricate data solution, provide the power through agile views.  SAP HANA streamlines the access to the data and provides a powerful solution.  This way, IT can manage the data model while the end users manage the business rules.

Furthermore, integrate your analytics with your SAP systems.  Direct integration is now available for SAP Business Planning and Consolidation.

SAP’s vision for the cloud for analytics:

  • Provide the full scope of analytics tasks in one place, including BI (Business Intelligence), planning, dashboards & visualization, predictive analytics, GRC (Governance, Risk, and Compliance), security, and administration.

  • Deliver the solution in the cloud as a service.  SAP manages the complexities behind the scenes.

  • Integrate applications into cloud for analytics (SuccessFactors, hybris, C4C (Cloud for Customer), Concur, Ariba, etc.).

  • Simplify delivery by using SAP HANA as a powerful foundation for high performance and real-time analysis.
  • Provide a consumer grade product with service focused on the business user.


Connect and prepare data.  Explore, search, and visualize the data.  Share your results.


Integration with BPC.  Expansion of simplify, experience, and trust.

Visualization & Storytelling

Personalize your home screen with interactive tiles, colorful charts and graphs, and collaboration panels.  Focus on best practices for visualizations for business data.  Customize charts to match your organization’s standards.  A large array of visualization options are provided.  Drill-down capabilities allow you to get into the details and follow the story.

Predictive Analytics

Data mining is provided to model cloud and on premise data from your browser.  End to end modeling is made easy and intuitive.  Machine learning provides auto-generated insights.  This makes it easy to find your “unknown unknowns.”  With the highly visualized displays, you get insight to action faster with powerful statistics that are easy to understand.


Build a story with your data with a single visualization application.  Personalize KPIs, dashboards, and storyboards.  Increase collaboration by providing a single point of reference for analytics.


With cloud solutions, there is an additional risk with security.

SAP provides a HANA cloud platform with single sign-on capabilities, where you can use your existing on premise authorizations in the cloud.  Using your current user groups, you can quickly configure CRUD authorization (Create, Read, Update, & Delete).

The big challenge for data analysts and scientists is during the initial phase of gathering and preparing data.  SAP HANA on the cloud detects data types, provides contextual suggestions for transformations, draws attention to potential data quality issues, and fits datasets into pre-existing models.

C4A Architecture

The C4A service allows you to connect powerful tools to your backend data.  There’s an option to connect to cloud data sources and on premise data sources.  When connecting to SAP HANA applications, you will use an online connection (remote).  The data will pass through C4A so you don’t have to replicate any data.  When connecting to other data sources, you will import the data into C4A for visualization and sharing.

After you connect to the data, you will prepare the data.  By preparing the data you will:

  • Ensure values in the columns meet user expectations
  • Provide meaningful names to attributes and measures
  • Make other types of semantic changes for an easier user experience

Through preparing the data, you create a data model that provides a foundation for business logic and visualizations.  Multiple users can now use the model for analytics and visualizations.