01

Analytics Foundation

Descriptive Statistics
  1. Measures of Central Location
  2. Relative Position of Data
  3. The Empirical Rule and Chebyshev’s Theorem
Basic Concepts of Probability
  1. Sample Spaces, Events, and Their Probabilities
  2. Complements, Intersections, and Unions
  3. Conditional Probability and Independent Events
Testing Hypotheses
  1. The Elements of Hypothesis Testing
  2. Large Sample Tests for a Population Mean
  3. The Observed Significance of a Test
  4. Small Sample Tests for a Population Mean
  5. Large Sample Tests for a Population Proportion
02

Data Visualization - Excel

  1. Filling Data
  2. Formula Referencing
  3. Creating Name Range
  4. Logical Functions
  5. Conditional Formatting
  6. Advanced Validation
  7. Formulas
  8. Dynamic Table
  9. Sorting Data
  10. Filtering Data
  11. Creating Charts
  12. Pivot Tables
  13. Dashboards – Visualization Best Practices
  14. Analysing Data
03

R for Business

  1. Introduction to R
  2. Introduction and exploring raw data
  3. Tidying data
  4. Preparing data for analysis
  5. Introduction to dplyr and tbls
  6. Select and mutate
  7. Filter and arrange
  8. Summarize and the pipe operator
  9. Group by and working with databases
  10. Mutating joins
  11. Filtering joins and set operations
  12. Assembling data
  13. Advanced joining
  14. Exploring Categorical Data
  15. Exploring Numerical Data
  16. Numerical Summaries
04

Data Visualization - Tableau

  1. Introducing Tableau 10.0
  2. Establishing Connection
  3. Joins and Union
  4. Data Blending
  5. Visual Analytics
  6. Highlighting
  7. Introduction to basic graphs
  8. Sorting Filtering Grouping
  9. Graphic Visualization
  10. Trend Lines Reference Lines
  11. Parameters
  12. Creating a Dashboard Layout
  13. Designing Dashboard for Devices
  14. Dashboard Interaction - Using Action
  15. Introduction to Maps
  16. Editing Unrecognized Locations
  17. Custom Geocoding
  18. Polygon Maps
  19. Web Mapping Services
  20. Background Images
  21. Different Functions
  22. Introduction to Table Calculation
  23. Fixed LOD , Included LOD, Excluded LOD
  24. Box and Whisker's Plots
  25. Gantt Waterfall Pareto Control Funnel Charts
05

Query Language for Business

  1. What is SQL
  2. Table Basics
  3. Selecting Data
  4. Creating Tables
  5. Inserting into a table
  6. Updating Records
  7. Deleting Records
  8. Drop a table
  9. Manipulation
  10. Select Clause
  11. Group By
  12. Having Clause
  13. Order By
  14. Combining Conditions & Boolean Operators
  15. In and Between
  16. Mathematical Functions
  17. Table Joins
06

Statistical Modelling

Domain Specific as per the specialization

07

Financial Analytics

Financial Ratios Using Analytical Tool
  1. Ratio analysis of industries
  2. Peer to peer analysis
  3. Preparation of Financial Analysis report on an industry
Project Based Financial Modeling
  1. Analyze Revenue Drivers
  2. Forecast Geographic & Segment Revenues
  3. Cost Statement, Debt, Income Statement, Balance Sheet, and Cash Flow Statement
  4. Compute Ratios
  5. Cash Flow Statement Projection
  6. Valuation- Discounted Cash Flow Method (DCF), Valuation – Relative Valuation (Football Field Chart)
  7. Valuation – Assumptions for Valuation Model
  8. Prepare Valuation Model
  9. Prepare Presentation Sheet
  10. Prepare Company Overview
  11. Sector Overview
08

HR Analytics

Stages of People Analytics
  1. Reporting
  2. Importance of Metrics
  3. Accountability and Measurement
  4. Metrics / KPI Model
  5. HR Metric Levels
  6. Enhancing PEOPLE Analytics Effectiveness
  7. Factors affecting after the implementation
  8. Used Case example
HRIS
  1. Need for HRIS
  2. HRIS absence and its impact
  3. Application of HRIS
  4. Example of HRIS In Action
  5. PEOPLE Data and its accessibility
  6. HRM Data Sources
  • Step by Step: Creating People Data Dashboard
  • Calculating PEOPLE Metrics / KPI’s
  • Analysing employee salary and performance data
09

Marketing Analytics

Metrics for Marketing Management
  1. Metrics for Brand Management
  2. Metrics for Product Management
  3. Metrics for Sales Management
Marketing Mix Models
  1. Market Response Models and their types
  2. Simple Market Response Models
  3. Marketing Mix Elements and Interactions
Predictive Models in Marketing
  1. Forecasting
  2. Propensity to Buy and Propensity to Churn
  3. Techniques for prediction such as Decision Trees and Logistic regression
Customer Segmentation Techniques
  1. The Segmentation Process
  2. Segmentation Research
  3. Segmentation Methods (Cluster Analysis and behaviour based Segmentation?
10

Operations Analytics

  • Supply Chain Drivers and Metrics
  • Basics of Linear Programming and Problem Solving
  • Network Design
  • Inventory Optimisation
  • Transportation Optimization

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