SAP Analytics Cloud (SAC) – Overview
Discover SAP Analytics Cloud (SAC) and how its business intelligence, planning, predictive analytics, data visualization, and integration capabilities enable data-driven decisions.

Introduction
What is SAP Analytics Cloud?
- SAP BW, SAP Universe, SAP HANA, Google BigQuery, SAP BPC, and SQL-based data sources.
- SAP S/4HANA, SAP BPC Embedded, and SAP Data Warehouse Cloud.
- Cloud applications such as SAP SuccessFactors, SAP Concur, and Qualtrics.
- The core layer is the base of the SAC platform. It has the SAP HANA database, the SAP Analytics Cloud application server, and the SAP Analytics Cloud web application.
- The data layer lets SAC connect to different data sources, such as SAP applications, data sources on your premises, and data sources in the cloud.
- The user layer is the interface for users to work with SAC. It has the SAP Analytics Cloud web application, the SAP Analytics Cloud mobile app, and the SAP Analytics Cloud SDK.

Key Features:




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Benefits of SAP Analytics Cloud
- Single sign-on (SSO): SAC works with SSO with different identity providers, such as SAML and OAuth. This lets users sign in to SAC with one set of credentials, which makes the authentication process easier and lowers the chance of unauthorized access.
- Role-based access control (RBAC): SAC uses RBAC to manage access to data and features. This lets administrators create different roles for users, with each role having different access levels.
- Fine-grained access control (FGAC): FGAC lets administrators manage access to specific data items. This is helpful for protecting sensitive data, such as customer PII.
Encryption and data protection methods:
- Data encryption: SAC uses encryption to secure data in transit and at rest. This makes sure that data is safe from unauthorized access and breaches.
- Data masking: SAC supports data masking, which lets administrators hide sensitive data. This is helpful for sharing data with external users without losing its confidentiality.
- Auditing: SAC offers auditing capabilities, which let administrators monitor user activity. This can be used to look into security incidents and to make sure that data is being accessed and used according to company policy.
- Additional security features: SAC also supports other security measures, such as password policies, security alerts, and two-factor authentication. These measures help to secure data from unauthorized access and ensure the safety of the SAC platform.
Use Cases:
- Financial Analysis: SAC enables finance teams to consolidate financial data from multiple sources, perform variance analysis, and create insightful financial reports and dashboards. Finance teams may combine financial data from many sources, carry out variance analysis, and produce meaningful financial reports and dashboards using SAC.
- Sales and Marketing Analytics: SAC empowers sales and marketing teams to analyze customer data, track sales performance, and identify trends and opportunities for revenue growth. SAC gives sales and marketing teams the tools they need to analyse client information, monitor sales progress, spot patterns and chances for revenue expansion.
- Supply Chain Optimization: SAC assists organizations in optimizing inventory levels, forecasting demand, and enhancing overall supply chain effectiveness by integrating data from diverse supply chain systems.
Recent Update features:
- Unified Stories and Analytic Applications: The unification of stories and analytic applications into one single artifact based on the optimized story experience. This provides usability and performance improvements, as well as new capabilities such as integrated design time, unified bookmark workflow, flexible theme and CSS, and more.
- Running Totals in Tables and Charts: The support for running total calculations (SUM, Average, Max, Min, Count) in tables and charts in stories. This is useful for tracking cumulative or running key KPIs.
- Planning Workflow Enhancements: The quality improvements on progress/status aggregation and concurrent editing notification for planning processes. This helps to streamline the planning workflow and collaboration among users.
- Data Point Commenting for Live SAP BW: The support for data point commenting for live SAP BW data sources. This allows users to add comments to specific data points in charts and tables and share them with other users.
- Integration of SAP Datasphere and SAP SAC: The integration of SAP Datasphere (formerly DWC) and SAP SAC marks a significant advancement, enabling users to seamlessly access and analyze data from various sources within a unified platform.
- Support for Custom Data Sources: The support for custom data sources that are not natively supported by SAC using data connectors. This allows users to connect to any data source that has an API or a JDBC driver.
- Enhanced Custom Widgets: The enhancement of custom widgets with data binding, widget dynamic visibility, size and position, and configurable runtime toolbar and context menu. This enables users to create more interactive and customized visualizations in stories and analytic applications.
- Advanced Story Design Features: The support for vertical filter panel, linked widgets diagram, data analyzer integration, last refreshed date and time, dynamic text for BW live data model, scheduling, and mobile support in the optimized story experience. This provides more flexibility and functionality for story design and consumption.































