SAP Analytics Cloud is a robust, agile analytics platform. It can integrate the existing business apps; connect databases and different information sources. It can handle enterprise-level Internet of Things information, create analyzed visual output with segregated data and deliver consistent insights to the business that is easily accessible in the cloud.
Some of the benefits of SAP Analytics Cloud for medium and large-sized entities are: collaborative planning, generate data insights for faster and better business decision-making, a higher value from existing investments, easy communication, improved business performance, predictive analytics, faster return on investment, single source of data truth, customized dashboard, etc.
At Shreyansh Techtraining institute, we will provide guidance, support, and advice on all the matters relating to your course right from the day you enroll. Our trainers are highly committed to your success in the industry, and they will help you earn industry-recognized qualifications and required skills. Commit yourself to a bright future.
SAP ANALYTICS CLOUD(SAC)
UNIT-1: Overview & Positioning
- SAP Analytics Cloud Architecture Overview
- SAC vs other BI tools
- Benefits & core functionalities of SAC
- Cloud vs On-Premise vs Hybrid
- SAP Analytic Cloud Client tools and Importance
UNIT-2: Connections
- Overview of Connections
- Live Connections
- Import Connections
- Connecting and accessing Flat file data
- Connecting and accessing Cloud applications
- Connecting and accessing Cloud databases
- Connecting and accessing SAP-HANA
- Connecting and accessing Odata services
UNIT-3: 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-4: Business Intelligence
- Desinging SAC Stories
- Working with Custom Templates
- Working with Standard Templates
- Working with Canvas-Responsive & 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 Table widget
- Working with Geo Map widget
- R language basics
- Generating R based Stories
UNIT-5: Augmented Analytics
- What is Augmented Analytics
- Smart Search
- Smart Discovery
- Smart Insights
UNIT-6: Analytics Designer
- What is SAP Analytics Designer
- Difference between SAC Stories vs SAP Analytics Designer
- Analytics Designer overview and walkthrough
- Outline,Designer,Error & reference panels
- Design mode vs Run mode vs View mode
- Desingning basic Analytic application
- working with Container widgets
- Implementing filters
- working with Drop-down,Radibutton,Checkbox componets
- working with script variables
- working with script objects
- Configuring and implementing Dynamic Visibility
- Working with Loop functions and Conditional Statements
- Implementing Hyperlinking and Explorer option
UNIT-7: Predictive Scenario
- Predictive scenario overview
- SAC Stories vs SAC Applications vs SAC Predictive
- Working with Datasets,Variables
- Implementing Classification Precitive Model
- Implementing Regression Predictive Model
- Implementing Timeseries Predictive Model
- Generating predictive stories
UNIT-8: Administration
- SAC Architecture Overview
- Working with Roles(Standard vs Custom)
- Defining Team(s)
- Defining User(s)
- Working with dataloading and scheduling
- SAP Cloud connector
- SAP Analyics Cloud Agent
- SAC Lifecycle management/Transports
UNIT-9: SAC Roadmap & Certification
- SAC Roadmaps(Current vs Future)
- SAC Project Implementation landscapes
- SAC Certification Overview
- ECC/BW/BO/S4-HANA/HANA-> SAC Migration Strategy
UNIT-10: SAC Planning
- SAC Planning Overview
- Building a Planning model
- Currency Table Configuration
- Working with Value Driver Tree
- Working with Data actions
- Working with Data actions
- Configuring allocations
- Working with Distributions
- Predictive forecasting implementation
- Generating Stories using planning models
- Generating analytic applications using planning models