Curriculum
- 19 Sections
- 339 Lessons
- 10 Weeks
Expand all sectionsCollapse all sections
- Introduction to Business Decision Making3
- Introduction to Business Analytics23
- 2.11- Definition and Scope of Business Analytics
- 2.2Business Analytics (BA)
- 2.3Data Collection and Integration
- 2.4Data Cleaning and Preprocessing
- 2.5Descriptive Analytics
- 2.6Data Exploration and Visualization
- 2.7Predictive Analytics
- 2.8Prescriptive Analytic
- 2.9Optimization and Simulation
- 2.10Text and Sentiment Analysis
- 2.11Data Governance and Securit
- 2.12Business Intelligence (BI)
- 2.132- Importance of Data-Driven Decision-Making
- 2.14Informed Decision-Making
- 2.15Competitive Advantage
- 2.16Cost Efficiency
- 2.17Customer Understanding
- 2.18Risk Management
- 2.19Strategic Planning
- 2.20Continuous Improvement
- 2.21Measurable Outcomes
- 2.22Case Studies
- 2.23Rest
- Key Concepts in Business Analytics14
- 3.1Data Collection and Storage
- 3.2Data Cleaning and Preprocessing
- 3.3Descriptive Analytics
- 3.4Predictive Analytics
- 3.5Prescriptive Analytics
- 3.6Business Intelligence (BI)
- 3.7Data Governance and Security
- 3.8Big Data Analytics
- 3.9Key Performance Indicators (KPIs)
- 3.10Data-driven Decision Making
- 3.11Agile Analytics
- 3.12Ethics in Analytics
- 3.13Rest
- 3.14Case Studies
- Tools and Technologies4
- Data Types and Sources17
- 5.11- Data Types
- 5.2Structured Data
- 5.3Unstructured Data
- 5.42- Data Sources
- 5.5Internal Data Sources
- 5.6External Data Sources
- 5.73- Data Collection Methods
- 5.8Surveys and Questionnaires
- 5.9Observation
- 5.10Interviews
- 5.11Sensor Data
- 5.12Web Scraping
- 5.13Transaction Data
- 5.14Social Media Monitoring
- 5.15Secondary Data Analysis
- 5.16Case Studies
- 5.17Rest
- Cleaning and Transformation25
- 6.11- Dealing with Missing Data
- 6.2Identification of Missing Values
- 6.3Removal of Missing Values
- 6.4Imputation of Missing Values
- 6.5Evaluate the Impact
- 6.6Documentation
- 6.7Iterative Process
- 6.82- Outlier Detection and Treatment
- 6.9Identification
- 6.10Removal
- 6.11Transformation
- 6.12Winsorizing
- 6.133- Data Normalization and Standardization
- 6.14Normalization (Min-Max Scaling)
- 6.15Standardization (Z-score Normalization)
- 6.16Robust Scaling (IQR Scaling)
- 6.174- Feature Engineering Techniques
- 6.18Binning/Discretization
- 6.19One-Hot Encoding
- 6.20Polynomial Features
- 6.21Interaction Terms
- 6.22Feature Scaling
- 6.23Dimensionality Reduction
- 6.24Case Studies
- 6.25Rest
- Predictive Modeling with SPSS9
- Exploratory Data Analysis (EDA) with SPSS16
- 8.1Introduction
- 8.21- Basic Statistical Analysis
- 8.3Descriptive Statistics
- 8.4Frequency Distribution
- 8.5Central Tendency and Dispersion
- 8.6Correlation Analysis
- 8.7Inferential Statistics
- 8.82- Data Visualization Technique
- 8.9Histograms
- 8.10Box Plots
- 8.11Scatter Plots
- 8.12Bar Charts
- 8.13Heatmaps
- 8.14Pie Charts
- 8.15Line Chart
- 8.16When should I use them?
- Statistical analysis with SPSS24
- 9.11- Descriptive Statistics
- 9.2Measures of Central Tendency and Dispersion
- 9.3Mean, Median, and Mode
- 9.4Variability Measures
- 9.51-2 Frequency Distributions
- 9.6Histograms
- 9.7Percentiles and Quartiles
- 9.81-3 Probability Distributions
- 9.9Normal Distribution
- 9.102- Inferential Statistics
- 9.112-1 Hypothesis Testing
- 9.12Formulate Hypotheses
- 9.13Conduct Statistical Tests
- 9.142-2 Confidence Intervals
- 9.153-1 Confidence Intervals
- 9.16Confidence Interval for Mean
- 9.174-1 Regression Analysis
- 9.18Simple Linear Regression
- 9.19Multiple Regression
- 9.205-1 Correlation Analysis
- 9.21Pearson Correlation
- 9.22SPSS Functionality
- 9.23When should I use them?
- 9.24Case Studies
- Prescriptive Analytics with SPSS8
- Business Intelligence and Reporting33
- 11.11- Dashboard and Visualization Design
- 11.21-1 Principles of Effective Data Visualization
- 11.3Clarity and Simplicity
- 11.4Relevance
- 11.5Consistency
- 11.6Interactivity
- 11.7Storytelling
- 11.8Use of Appropriate Visualization Types
- 11.9Color Usage
- 11.10Data Accuracy and Precision
- 11.111-2 Dashboard Development and Best Practices
- 11.12Define Objectives
- 11.13User-Centric Design
- 11.14Performance Optimization
- 11.15Responsive Design
- 11.16Feedback Mechanisms
- 11.17Regular Updates
- 11.18Testing and Validation
- 11.192- Reporting Tools
- 11.202-1 Introduction to Reporting Tools
- 11.21Tableau
- 11.22Power BI (Microsoft Power BI)
- 11.232-2 Creating Dynamic and Interactive Reports
- 11.24Data Connection
- 11.25Report Design
- 11.26Interactivity
- 11.27Data Refresh and Automation
- 11.28Collaboration and Sharing
- 11.29Security and Access Control
- 11.30Documentation and Training
- 11.31Case Studies
- 11.32Rest
- 11.33Contact Form
- Decision Making Models34
- 12.11- Rational Decision Making Model
- 12.2Problem Identification Module
- 12.3Alternative Generation Module
- 12.4Alternative Evaluation Module
- 12.5Alternative Selection Module
- 12.6Implementation Module
- 12.7Monitoring and Evaluation Module
- 12.82- Bounded Rationality
- 12.9Constraint Recognition Module
- 12.10Satisficing Objective Module
- 12.11Heuristic Utilization Module
- 12.12Risk Assessment Module
- 12.13Adaptive Learning Module
- 12.143- Intuitive Decision Making
- 12.15Intuition Recognition Module
- 12.16Expertise Utilization Module
- 12.17Situation Assessment Module
- 12.18Bias Awareness Module
- 12.19Supplementary Rational Analysis Module
- 12.204- Normative Decision Theory
- 12.21Assumption Identification Module
- 12.22Criterion Specification Module
- 12.23Logical Coherence Assessment Module
- 12.24Rationality Evaluation Module
- 12.25Decision Prescription Module
- 12.265- Behavioral Decision Making
- 12.27Psychological Factors Identification Module
- 12.28Social Influence Recognition Module
- 12.29Cognitive Bias Awareness Module
- 12.30Emotional Influence Module
- 12.31Heuristic Utilization Module
- 12.32Bias Mitigation Strategies Module
- 12.33Case Stdies
- 12.34Rest
- Risk Management and Uncertainty33
- 13.11- Identifying Risks
- 13.2Threat Recognition Module
- 13.3Source Analysis Module
- 13.4Environmental Scan Module
- 13.5Risk Cataloging Module
- 13.6Risk Impact Assessment Module
- 13.7Risk Probability Assessment Module
- 13.8Risk Interdependency Analysis Module
- 13.92- Risk Assessment
- 13.10Probability Assessment Module
- 13.11Source Analysis Module:
- 13.12Environmental Scan Module
- 13.13Risk Cataloging Module
- 13.14Risk Impact Assessment Module
- 13.15Scenario Analysis Module
- 13.163- Risk Analysis Techniques
- 13.17Quantitative Analysis Module
- 13.18Qualitative Analysis Module
- 13.19Scenario Analysis Module
- 13.20Sensitivity Analysis Module
- 13.214- Risk Mitigation Strategies
- 13.22Avoidance Strategy Module
- 13.23Reduction Strategy Module
- 13.24Transfer Strategy Module
- 13.25Acceptance Strategy Module
- 13.265- Monitoring and Review
- 13.27Effectiveness Tracking Module
- 13.28Risk Identification Module
- 13.29Adaptation and Adjustment Module
- 13.30Communication and Reporting Module
- 13.31Continuous Improvement Module
- 13.32Case Studies
- 13.33Rest
- Cost-Benefit Analysis36
- 14.11- Identifying Costs and Benefits
- 14.2Direct Costs Identification
- 14.3Indirect Costs Identification
- 14.4Benefit Identification
- 14.5Monetary Valuation
- 14.6Non-Monetary Valuation
- 14.72- Quantifying Costs and Benefits
- 14.8Direct Cost Quantification
- 14.9Indirect Cost Quantification
- 14.10Benefit Quantification
- 14.11Complex Analysis and Estimation Techniques
- 14.123- Discounting Future Costs and Benefits
- 14.13Time Value of Money
- 14.14Discount Rate
- 14.15Discounting Future Costs and Benefits
- 14.16Inflation Adjustment
- 14.17Sensitivity Analysis
- 14.18Net Present Value (NPV)
- 14.194- Calculating Net Present Value (NPV)
- 14.20Identifying Cash Flows
- 14.21Discounting Future Cash Flows
- 14.22Summing Present Values
- 14.23Interpreting NPV
- 14.24Interpreting NPV
- 14.25Sensitivity Analysis
- 14.265- Sensitivity Analysis
- 14.27Identifying Key Variables
- 14.28Defining Ranges for Variation
- 14.29Selecting the Sensitivity Analysis Method
- 14.30Conducting One-Way Sensitivity Analysis
- 14.31Conducting Multi-Way Sensitivity Analysis
- 14.32Interpreting Results
- 14.33Scenario Analysis
- 14.34Risk Mitigation and Decision-Making
- 14.35Case Studies
- 14.36Rest
- Decision Trees and Scenario Analysis2
- Game Theory and Strategic Decision Making10
- Ethical Decision Making10
- Implementation and Monitoring12
- Decision Making in Cross-functional Teams26
- 19.11- Benefits of Cross-functional Teams
- 19.2Diverse Perspectives
- 19.3Specialized Expertise
- 19.4Improved Decision Making
- 19.5Enhanced Communication
- 19.62- Challenges of Decision Making in Cross-functional Teams
- 19.7Conflicting Priorities
- 19.8Communication Barriers
- 19.9Differing Viewpoints
- 19.103- Dynamics of Decision Making in Cross-functional Teams
- 19.11Power Dynamics
- 19.12Group Dynamics
- 19.13Individual Personalities
- 19.144- Techniques for Effective Collaboration
- 19.15Active Listening
- 19.16Consensus-Building
- 19.17Conflict Resolution
- 19.18Tools and Methodologies
- 19.195- Decision-making Techniques for Cross-functional Teams
- 19.20Multi-voting
- 19.21Decision Matrices
- 19.22RAPID Framework (Responsible, Accountable, Consulted, Informed)
- 19.23Case Studies
- 19.24Rest
- 19.25Exam
- 19.26Contact Form