SAP Analytics Cloud(SAC)

UNIT-1: Overview and Positioning
 Analytics Cloud Architecture Overview
 SAC vs other BI tools
 Benefits and core functionalities of SAC
 Cloud vs On-Premise vs Hybrid
 Analytics Cloud Client tools and Importance

UNIT-2: Modelling
 What is MODEL
 Components of MODEL
 Working with Dimension and Classification
 Configuring Geo-Dimension
 Working with Measures
 Working with Transformations
 Working with Variables
 Data Blending

UNIT-3: Business Intelligence
 Designing SAC Stories
 Working with Custom Templates
 Working with Standard Templates
 Working with Canvas-Responsive and Grid modes
 Working with Designer (Builder panel, Styling Panel)
 Filters in SAC
 Query level filters
 Story level filters
 Page-level filters
 Widget level filters
 Advanced Filters

 Linked Analysis
 Hyperlinking
 Conditional Formatting
 Customizing Measures
 Customizing Dimensions
 Data blending
 Working with Chart widget
 Working with a Table widget
 Working with Geo Map widget
 R language basics
 Generating R based Stories
 Import data connection from Google drive

UNIT-4 Augmented Analytics
 What is Augmented Analytics
 Smart Search
 Smart Discovery
 Smart Insights

UNIT-5: Planning with SAC
 How to develop planning data models in SAC
 Understand measures, accounts, hierarchies, currency conversion
 Manage versions of planning
 Create planning stories
 Planning functions – variance, forecast, version management
 What if analysis
 Allocations
 Spreading and Distributions
 Value Driver Tree- VDT
 Data actions and insights
 Live Data connection to BPC system
 Collaboration

UNIT-6: Analytics Designer
 What is Analytics Designer
 Difference between SAC Stories vs Analytics Designer
 Analytics Designer overview and walkthrough
 Outline, Designer, Error, and reference panels
 Design mode vs Run mode vs View mode

 Designing basic Analytic application
 working with Container widgets
 Implementing filters
 working with Drop-down, Radio button, Checkbox components
 working with script variables
 working with script objects
 Configuring and implementing Dynamic Visibility
 Implementing Hyperlinking and Explorer option
 Using APIs to integration with Smart discovery, smart insights
 Embedding the webpages inside the Analytic designer
 Embedding SAC app inside other webpages
 Live Data connection to Application Program ON HDB for integration
 Close loop scenarios with OData Integration

UNIT-7: Predictive Scenario
 Predictive scenario overview
 SAC Stories vs SAC Applications vs SAC Predictive
 Working with Datasets, Variables
 Understand Regression
 Understand Logistic Regression, RoC Curves, AUC Curve
 Model performance and Confusion Matrix
 Profit Simulation for Classification
 Implementing Classification Precative Model
 Implementing Regression Predictive Model
 Residual and MAPE Concept in Regression
 Trend, Cycle, Residual and Variations concepts
 Implementing a Time series Predictive Model
 Generating predictive stories

UNIT-8: Administration
 SAC Administration Overview
 Roles (Standard vs Custom)
 Team
 Users
 Working with data loading and scheduling
 Cloud connector
 Analytics Cloud Agent

UNIT-9: SAC Roadmap and Certification