Visit This Web URL https://masterytrail.com/product/accredited-expert-level-sap-enterprise-demand-sensing-advanced-video-course Lesson 1.Overview of SAP Enterprise Demand Sensing
1.1.1 Introduction to Demand Sensing
1.1.2 Importance in Supply Chain
1.1.3 Key Features
1.1.4 Benefits of Implementation
1.1.5 Case Studies
1.1.6 Integration with Other SAP Modules
1.1.7 User Interface Overview
1.1.8 Basic Navigation
1.1.9 System Requirements
1.1.10 Initial Setup and Configuration
Lesson 1.2: Understanding Demand Sensing Concepts
1.2.1 Definition and Scope
1.2.2 Demand Sensing vs. Demand Planning
1.2.3 Data Sources and Types
1.2.4 Real-time Data Processing
1.2.5 Demand Signal Repository
1.2.6 Statistical Models
1.2.7 Machine Learning Integration
1.2.8 Forecast Accuracy Metrics
1.2.9 Demand Variability Management
1.2.10 Best Practices
Lesson 1.3: Installation and Configuration
1.3.1 Pre-installation Checklist
1.3.2 Installation Steps
1.3.3 Post-installation Configuration
1.3.4 System Landscape
1.3.5 User Roles and Permissions
1.3.6 Integration with SAP ERP
1.3.7 Data Migration
1.3.8 Initial Data Load
1.3.9 System Validation
1.3.10 Troubleshooting Installation Issues
Lesson 1.4: User Interface and Navigation
1.4.1 Dashboard Overview
1.4.2 Menu Navigation
1.4.3 Customizing Views
1.4.4 Search and Filter Options
1.4.5 Personalization Settings
1.4.6 Shortcuts and Tips
1.4.7 Mobile Accessibility
1.4.8 Reporting Tools
1.4.9 Alerts and Notifications
1.4.10 User Preferences
Module 2: Data Management and Integration
Lesson 2.1: Data Sources and Integration
2.1.1 Types of Data Sources
2.1.2 Data Integration Techniques
2.1.3 Real-time Data Feeds
2.1.4 Data Cleansing
2.1.5 Data Transformation
2.1.6 Data Enrichment
2.1.7 Data Validation
2.1.8 Data Storage
2.1.9 Data Security
2.1.10 Data Governance
Lesson 2.2: Data Modeling and Analysis
2.2.1 Data Modeling Basics
2.2.2 Statistical Analysis
2.2.3 Predictive Analytics
2.2.4 Machine Learning Models
2.2.5 Data Visualization
2.2.6 Scenario Analysis
2.2.7 Sensitivity Analysis
2.2.8 Demand Pattern Recognition
2.2.9 Anomaly Detection
2.2.10 Model Optimization
Lesson 2.3: Demand Sensing Configuration
2.3.1 Configuration Overview
2.3.2 Setting Up Data Sources
2.3.3 Configuring Data Models
2.3.4 Defining Business Rules
2.3.5 Setting Up Alerts
2.3.6 Configuring Reports
2.3.7 User Access Control
2.3.8 System Parameters
2.3.9 Integration Settings
2.3.10 Validation and Testing
Lesson 2.4: Advanced Data Processing
2.4.1 Real-time Data Processing
2.4.2 Batch Processing
2.4.3 Data Aggregation
2.4.4 Data Segmentation
2.4.5 Data Enrichment Techniques
2.4.6 Data Quality Management
2.4.7 Data Integration Tools
2.4.8 Data Transformation Tools
2.4.9 Data Analysis Tools
2.4.10 Data Visualization Tools
Module 3: Demand Sensing and Forecasting
Lesson 3.1: Demand Sensing Techniques
3.1.1 Introduction to Demand Sensing Techniques
3.1.2 Real-time Demand Sensing
3.1.3 Historical Data Analysis
3.1.4 Market Trends Analysis
3.1.5 Customer Behavior Analysis
3.1.6 Competitor Analysis
3.1.7 Demand Pattern Recognition
3.1.8 Anomaly Detection
3.1.9 Demand Segmentation
3.1.10 Demand Sensing Best Practices
Lesson 3.2: Forecasting Models
3.2.1 Introduction to Forecasting Models
3.2.2 Time Series Analysis
3.2.3 Regression Analysis
3.2.4 Machine Learning Models
3.2.5 Predictive Analytics
3.2.6 Scenario Analysis
3.2.7 Sensitivity Analysis
3.2.8 Forecast Accuracy Metrics
3.2.9 Model Optimization
3.2.10 Forecasting Best Practices
Lesson 3.3: Demand Planning and Execution
3.3.1 Introduction to Demand Planning
3.3.2 Demand Planning Process
3.3.3 Demand Planning Tools
3.3.4 Demand Planning Techniques
3.3.5 Demand Planning Best Practices
3.3.6 Demand Execution Process
3.3.7 Demand Execution Tools
3.3.8 Demand Execution Techniques
3.3.9 Demand Execution Best Practices
3.3.10 Integration with Supply Chain
Lesson 3.4: Advanced Demand Sensing
3.4.1 Introduction to Advanced Demand Sensing
3.4.2 Real-time Demand Sensing Techniques
3.4.3 Advanced Data Analysis
3.4.4 Advanced Machine Learning Models
3.4.5 Advanced Predictive Analytics
3.4.6 Advanced Scenario Analysis
3.4.7 Advanced Sensitivity Analysis
3.4.8 Advanced Forecast Accuracy Metrics
3.4.9 Advanced Model Optimization
3.4.10 Advanced Demand Sensing Best Practices
Module 4: Integration and Optimization
Lesson 4.1: Integration with SAP Modules
4.1.1 Introduction to SAP Integration
4.1.2 Integration with SAP ERP
4.1.3 Integration with SAP SCM
4.1.4 Integration with SAP CRM
4.1.5 Integration with SAP BW
4.1.6 Integration with SAP HANA
4.1.7 Integration with SAP Fiori
4.1.8 Integration with SAP S/4HANA
4.1.9 Integration with SAP IBP
4.1.10 Integration Best Practices
Lesson 4.2: System Optimization
4.2.1 Introduction to System Optimization
4.2.2 Performance Tuning
4.2.3 Data Optimization
4.2.4 Model Optimization
4.2.5 Process Optimization
4.2.6 Resource Optimization
4.2.7 Cost Optimization
4.2.8 Time Optimization
4.2.9 Quality Optimization
4.2.10 Optimization Best Practices
Lesson 4.3: Advanced Reporting and Analytics
4.3.1 Introduction to Advanced Reporting
4.3.2 Advanced Reporting Tools
4.3.3 Advanced Reporting Techniques
4.3.4 Advanced Data Visualization
4.3.5 Advanced Analytics Tools
4.3.6 Advanced Analytics Techniques
4.3.7 Advanced Scenario Analysis
4.3.8 Advanced Sensitivity Analysis
4.3.9 Advanced Forecast Accuracy Metrics
4.3.10 Advanced Reporting Best Practices
Lesson 4.4: Case Studies and Best Practices
4.4.1 Introduction to Case Studies
4.4.2 Case Study 1: Retail Industry
4.4.3 Case Study 2: Manufacturing Industry
4.4.4 Case Study 3: Healthcare Industry
4.4.5 Case Study 4: Financial Services
4.4.6 Case Study 5: Technology Sector
4.4.7 Best Practices in Retail
4.4.8 Best Practices in Manufacturing
4.4.9 Best Practices in Healthcare
4.4.10 Best Practices in Financial Services
Module 5: Advanced Topics and Future Trends
Lesson 5.1: Advanced Machine Learning in Demand Sensing
5.1.1 Introduction to Advanced Machine Learning
5.1.2 Machine Learning Models
5.1.3 Model Training and Validation
5.1.4 Model Optimization
5.1.5 Model Deployment
5.1.6 Model Monitoring
5.1.7 Model Maintenance
5.1.8 Model Interpretation
5.1.9 Model Evaluation
5.1.10 Machine Learning Best Practices
Lesson 5.2: Predictive Analytics and Forecasting
5.2.1 Introduction to Predictive Analytics
5.2.2 Predictive Analytics Techniques
5.2.3 Predictive Analytics Tools
5.2.4 Predictive Analytics Best Practices
5.2.5 Introduction to Forecasting
5.2.6 Forecasting Techniques
5.2.7 Forecasting Tools
5.2.8 Forecasting Best Practices
5.2.9 Integration with Demand Sensing
5.2.10 Future Trends in Predictive Analytics
Lesson 5.3: Real-time Data Processing and Analysis
5.3.1 Introduction to Real-time Data Processing
5.3.2 Real-time Data Processing Techniques
5.3.3 Real-time Data Processing Tools
5.3.4 Real-time Data Processing Best Practices
5.3.5 Introduction to Real-time Data Analysis
5.3.6 Real-time Data Analysis Techniques
5.3.7 Real-time Data Analysis Tools
5.3.8 Real-time Data Analysis Best Practices
5.3.9 Integration with Demand Sensing
5.3.10 Future Trends in Real-time Data Processing
Lesson 5.4: Future Trends in Demand Sensing
5.4.1 Introduction to Future Trends
5.4.2 Emerging Technologies
5.4.3 Artificial Intelligence and Machine Learning
5.4.4 Internet of Things (IoT)
5.4.5 Big Data Analytics
5.4.6 Cloud Computing
5.4.7 Blockchain Technology
5.4.8 Advanced Data Visualization
5.4.9 Integration with Other Systems
5.4.10 Future Trends in Demand Sensing
Module 6: Implementation and Project Management
Lesson 6.1: Project Planning and Management
6.1.1 Introduction to Project Planning
6.1.2 Project Scope Definition
6.1.3 Project Timeline
6.1.4 Resource Allocation
6.1.5 Risk Management
6.1.6 Stakeholder Management
6.1.7 Communication Plan
6.1.8 Project Monitoring and Control
6.1.9 Project Documentation
6.1.10 Project Closure
Lesson 6.2: System Implementation
6.2.1 Introduction to System Implementation
6.2.2 System Requirements
6.2.3 System Design
6.2.4 System Development
6.2.5 System Testing
6.2.6 System Deployment
6.2.7 System Integration
6.2.8 System Validation
6.2.9 System Training
6.2.10 System Go-Live
Lesson 6.3: Change Management
6.3.1 Introduction to Change Management
6.3.2 Change Management Process
6.3.3 Change Management Tools
6.3.4 Change Management Techniques
6.3.5 Change Management Best Practices
6.3.6 Stakeholder Engagement
6.3.7 Communication Plan
6.3.8 Training and Support
6.3.9 Monitoring and Evaluation
6.3.10 Change Management Success Factors
Lesson 6.4: Post-Implementation Review
6.4.1 Introduction to Post-Implementation Review
6.4.2 Review Objectives
6.4.3 Review Process
6.4.4 Review Tools
6.4.5 Review Techniques
6.4.6 Review Best Practices
6.4.7 Stakeholder Feedback
6.4.8 Performance Metrics
6.4.9 Lessons Learned
6.4.10 Continuous Improvement
Module 7: Advanced Configuration and Customization
Lesson 7.1: Advanced Configuration Techniques
7.1.1 Introduction to Advanced Configuration
7.1.2 Configuration Tools
7.1.3 Configuration Techniques
7.1.4 Configuration Best Practices
7.1.5 Customizing User Interface
7.1.6 Customizing Reports
7.1.7 Customizing Alerts
7.1.8 Customizing Dashboards
7.1.9 Customizing Workflows
7.1.10 Customizing Integration
Lesson 7.2: Customizing Demand Sensing Models
7.2.1 Introduction to Customizing Models
7.2.2 Model Customization Techniques
7.2.3 Model Customization Tools
7.2.4 Model Customization Best Practices
7.2.5 Customizing Data Models
7.2.6 Customizing Statistical Models
7.2.7 Customizing Machine Learning Models
7.2.8 Customizing Predictive Models
7.2.9 Customizing Forecasting Models
7.2.10 Customizing Scenario Models
Lesson 7.3: Advanced Integration Techniques
7.3.1 Introduction to Advanced Integration
7.3.2 Integration Tools
7.3.3 Integration Techniques
7.3.4 Integration Best Practices
7.3.5 Integrating with SAP ERP
7.3.6 Integrating with SAP SCM
7.3.7 Integrating with SAP CRM
7.3.8 Integrating with SAP BW
7.3.9 Integrating with SAP HANA
7.3.10 Integrating with SAP Fiori
Lesson 7.4: Customizing Reports and Dashboards
7.4.1 Introduction to Customizing Reports
7.4.2 Report Customization Techniques
7.4.3 Report Customization Tools
7.4.4 Report Customization Best Practices
7.4.5 Customizing Dashboards
7.4.6 Dashboard Customization Techniques
7.4.7 Dashboard Customization Tools
7.4.8 Dashboard Customization Best Practices
7.4.9 Customizing Data Visualization
7.4.10 Customizing Alerts and Notifications
Module 8: Security and Compliance
Lesson 8.1: Data Security and Privacy
8.1.1 Introduction to Data Security
8.1.2 Data Security Techniques
8.1.3 Data Security Tools
8.1.4 Data Security Best Practices
8.1.5 Introduction to Data Privacy
8.1.6 Data Privacy Techniques
8.1.7 Data Privacy Tools
8.1.8 Data Privacy Best Practices
8.1.9 Compliance with Regulations
8.1.10 Data Protection Strategies
Lesson 8.2: System Security and Access Control
8.2.1 Introduction to System Security
8.2.2 System Security Techniques
8.2.3 System Security Tools
8.2.4 System Security Best Practices
8.2.5 Introduction to Access Control
8.2.6 Access Control Techniques
8.2.7 Access Control Tools
8.2.8 Access Control Best Practices
8.2.9 User Authentication
8.2.10 Role-Based Access Control
Lesson 8.3: Compliance and Auditing
8.3.1 Introduction to Compliance
8.3.2 Compliance Techniques
8.3.3 Compliance Tools
8.3.4 Compliance Best Practices
8.3.5 Introduction to Auditing
8.3.6 Auditing Techniques
8.3.7 Auditing Tools
8.3.8 Auditing Best Practices
8.3.9 Compliance with Regulations
8.3.10 Audit Trails and Logging
Lesson 8.4: Risk Management and Mitigation
8.4.1 Introduction to Risk Management
8.4.2 Risk Management Techniques
8.4.3 Risk Management Tools
8.4.4 Risk Management Best Practices
8.4.5 Introduction to Risk Mitigation
8.4.6 Risk Mitigation Techniques
8.4.7 Risk Mitigation Tools
8.4.8 Risk Mitigation Best Practices
8.4.9 Risk Assessment
8.4.10 Risk Monitoring and Control
Module 9: Advanced Analytics and Visualization
Lesson 9.1: Advanced Data Analytics
9.1.1 Introduction to Advanced Data Analytics
9.1.2 Advanced Data Analytics Techniques
9.1.3 Advanced Data Analytics Tools
9.1.4 Advanced Data Analytics Best Practices
9.1.5 Data Mining Techniques
9.1.6 Data Mining Tools
9.1.7 Data Mining Best Practices
9.1.8 Predictive Analytics Techniques
9.1.9 Predictive Analytics Tools
9.1.10 Predictive Analytics Best Practices
Lesson 9.2: Advanced Data Visualization
9.2.1 Introduction to Advanced Data Visualization
9.2.2 Advanced Data Visualization Techniques
9.2.3 Advanced Data Visualization Tools
9.2.4 Advanced Data Visualization Best Practices
9.2.5 Customizing Dashboards
9.2.6 Dashboard Customization Techniques
9.2.7 Dashboard Customization Tools
9.2.8 Dashboard Customization Best Practices
9.2.9 Data Storytelling Techniques
9.2.10 Data Storytelling Best Practices
Lesson 9.3: Advanced Reporting Techniques
9.3.1 Introduction to Advanced Reporting
9.3.2 Advanced Reporting Techniques
9.3.3 Advanced Reporting Tools
9.3.4 Advanced Reporting Best Practices
9.3.5 Customizing Reports
9.3.6 Report Customization Techniques
9.3.7 Report Customization Tools
9.3.8 Report Customization Best Practices
9.3.9 Automating Reports
9.3.10 Report Distribution Techniques
Lesson 9.4: Advanced Scenario Analysis
9.4.1 Introduction to Advanced Scenario Analysis
9.4.2 Advanced Scenario Analysis Techniques
9.4.3 Advanced Scenario Analysis Tools
9.4.4 Advanced Scenario Analysis Best Practices
9.4.5 Scenario Planning Techniques
9.4.6 Scenario Planning Tools
9.4.7 Scenario Planning Best Practices
9.4.8 Sensitivity Analysis Techniques
9.4.9 Sensitivity Analysis Tools
9.4.10 Sensitivity Analysis Best Practices
Module 10: Continuous Improvement and Innovation
Lesson 10.1: Continuous Improvement Techniques
10.1.1 Introduction to Continuous Improvement
10.1.2 Continuous Improvement Techniques
10.1.3 Continuous Improvement Tools
10.1.4 Continuous Improvement Best Practices
10.1.5 Process Optimization Techniques
10.1.6 Process Optimization Tools
10.1.7 Process Optimization Best Practices
10.1.8 Performance Monitoring Techniques
10.1.9 Performance Monitoring Tools
10.1.10 Performance Monitoring Best Practices
Lesson 10.2: Innovation in Demand Sensing
10.2.1 Introduction to Innovation
10.2.2 Innovation Techniques
10.2.3 Innovation Tools
10.2.4 Innovation Best Practices
10.2.5 Emerging Technologies in Demand Sensing
10.2.6 Artificial Intelligence and Machine Learning
10.2.7 Internet of Things (IoT)
10.2.8 Big Data Analytics
10.2.9 Cloud Computing
10.2.10 Blockchain Technology
Lesson 10.3: Advanced Training and Development
10.3.1 Introduction to Advanced Training
10.3.2 Advanced Training Techniques
10.3.3 Advanced Training Tools
10.3.4 Advanced Training Best Practices
10.3.5 Customizing Training Programs
10.3.6 Training Program Customization Techniques
10.3.7 Training Program Customization Tools
10.3.8 Training Program Customization Best Practices
10.3.9 Training Evaluation Techniques
10.3.10 Training Evaluation Best Practices
Lesson 10.4: Future Trends and Strategic Planning
10.4.1 Introduction to Future Trends
10.4.2 Emerging Technologies
10.4.3 Artificial Intelligence and Machine Learning
10.4.4 Internet of Things (IoT)
10.4.5 Big Data Analytics
10.4.6 Cloud Computing
10.4.7 Blockchain Technology
10.4.8 Advanced Data Visualization
10.4.9 Integration with Other Systems