Data Analysis (Basic - Intermediate - Advanced)
Build analytical power. Turn data into decisions. Scale insight across the organization.
- Format: In-person, live online, or blended
- Methodology: • Real datasets from finance, operations, customer, digital • Step-by-step lab activities • Case studies tailored to industry • Practical coaching and analytical review
In a business environment driven by speed, complexity, and digital transformation, the ability to analyze data effectively is no longer optional — it is a core capability for every modern organization.
Data Analysis (Basic • Intermediate • Advanced) is a modular learning journey designed to develop complete analytical proficiency across three levels:
•Basic: Excel Power Tools for fast and effective business analytics
•Intermediate: JMP or Minitab for structured statistical analysis and process optimization
•Advanced: R or Python for predictive analytics and machine learning
Each level builds progressively toward an end-to-end analytical mastery that enables participants to transform raw data into actionable insight, support strategic decision-making, and accelerate continuous improvement.
This course is ideal both for professionals starting their analytical journey and for experts who want to advance into predictive modeling and real data science applications.
Learning Journey Structure (Three Levels)
Level 1 – Basic
Learning Objectives
Participants will learn to:
Level 1 – Basic: Excel Power Tools
Fast, flexible, and powerful analytics using Excel.
Duration: 2 days
Project Work: Optional mini-dashboard exercise
Certification: Basic Data Analysis Certificate
- Prepare, clean, and transform data with Power Query
- Build data models using Power Pivot
- Use Excel Power Tools to automate business reporting
- Create pivot tables, dynamic dashboards, and drill-down views
- Apply descriptive statistics and basic forecasting
- Visualize data effectively for managers and teams
Level 2 – Intermediate: JMP / Minitab
Statistical thinking and analytical rigor for structured problem solving.
Learning Objectives
Participants will be able to:
- Conduct Exploratory Data Analysis (EDA)
- Apply statistical inference and hypothesis testing
- Perform regression, correlation, and ANOVA
- Visualize statistical results effectively
- Use control charts and process capability (Cp, Cpk)
- Integrate analytics with Lean Six Sigma improvement projects
Duration: 3 days
Project Work: Statistical analysis case study
Certification:Intermediate Data Analysis Certificate
Level 3 – Power BI (Business Intelligence) & Copilot/Chat GPT & SalesForce
Predictive analytics, machine learning, and automated insights.
Learning Objectives
Participants will learn to:
- Build advanced analytical workflows
- Perform predictive modeling for regression & classification
- Apply clustering and segmentation techniques
- Use machine learning algorithms (basic models)
- Create visualizations
- Automate analytical tasks and pipelines
- Integrate models into business processes
Duration: 3–4 days
Project Work: Build and present an analytical model
Certification: Advanced Data Analysis Certificate
Target Audience
This modular program is ideal for:
• Business Analysts & Data Analysts
• Lean Six Sigma Practitioners
• Process Owners & Operational Leaders
• Quality, Supply Chain & Manufacturing Managers
• Finance, Risk, and Compliance Teams
• Digital & Transformation Leaders
• Anyone involved in KPI reporting, insights, or data-driven decisions
Industries Served
The program is applicable across:
• Banking & Insurance – risk modeling, performance dashboards, forecasting
• Manufacturing – quality analytics, DOE, SPC, OEE performance modeling
• Asset Management & Financial Services – portfolio insights, data modeling
• Luxury & Retail – customer analytics, sales performance
• Healthcare & Pharma – statistical studies, compliance analytics
• Logistics & Services – demand forecasting, operational analytics
• Energy, Utilities, Public Sector – audit data, continuous improvement, KPI tracking
Certification
Participants receive:
• Basic Data Analysis Certificate
• Intermediate Statistical Analysis Certificate (JMP/Minitab)
• Advanced Data Science Certificate (R/Python)
A final recognition (Data Analysis Professional Certification) can be awarded upon completing all three levels + final project.
Course Content
- Data wrangling: cleaning, joining, shaping datasets
- Power Query automation pipelines
- Power Pivot models and DAX fundamentals
- Charts, slicers, KPI indicators
- Interactive dashboards for operational and managerial use
- EDA and visualization
- Hypothesis testing and confidence intervals
- Basic and multiple regression
- Capability studies (normal and non-normal data)
- Control charts selection and interpretation
- Experimental design (DOE) fundamentals
- Data preprocessing, wrangling, and feature engineering
- Regression, classification, clustering
- Model validation and performance metrics
- Visualization and dashboards
- Automated pipelines and reproducible code
- Use cases in finance, operations, customer analytics, risk, and process improvement
- Basic level: no prerequisites
- Intermediate level: familiarity with Excel and base statistics
- Advanced level: basic programming logic recommended (not mandatory)
- Build an end-to-end analytical capability — from Excel to Python.
- Strengthen your ability to support strategic decisions with real data.
- Increase productivity by automating reporting and analysis tasks.
- Support Lean, Agile, and Operational Excellence with quantitative insights.
- Develop a skillset highly valued in every industry undergoing digital transformation.
- Grow from business user → analyst → advanced data practitioner.
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Our team is at your service — contact us to discover how we can create tangible value for your business together.