About The Course

Become an Enterprise Data Professional for the AI Era
Industry-Oriented Professional Certification Program
The Master in Data Analytics, Data Governance & AI is a comprehensive, industry-focused program designed to prepare graduates, working professionals, and career changers for today's data-driven organizations. This program combines Data Analytics, Enterprise Data Governance, Cloud Fundamentals, and AI to build practical, job-ready skills aligned with modern enterprise requirements.

Unlike traditional analytics programs, this curriculum emphasizes not only analyzing data but also managing, governing, protecting, and enabling trusted data for AI-powered business decisions. Learners gain hands-on experience through real-world projects, industry case studies, and enterprise best practices.

Program Overview

Duration 4 Months (16 Weeks)
Live Training 128 Hours
Delivery Mode Live Online Instructor-Led
Projects Hands-on & Capstone
Framework DAMA-DMBOK Aligned
Level Beginner to Advanced

Why Choose This Program?

  • Comprehensive curriculum covering Analytics, Governance & AI
  • Industry-aligned learning with practical enterprise use cases
  • Hands-on projects and business case studies
  • DAMA-DMBOK aligned Data Governance concepts
  • Exposure to modern cloud and enterprise data platforms
  • Portfolio development through real-world assignments
  • Resume building, LinkedIn branding, and interview prep
  • Mentoring by experienced industry professionals
  • Designed for today's AI-enabled enterprise workforce

Program Highlights

  • 🎓 Comprehensive Industry-Focused Curriculum
  • 📊 Data Analytics, Data Governance & AI
  • 💻 Live Instructor-Led Online Training
  • 🛠️ Hands-on Projects & Enterprise Case Studies
  • 📈 Professional Portfolio Development
  • 📝 Resume Building & Interview Preparation
  • 👨‍🏫 Mentoring by Industry Experts
  • ☁️ Cloud & AI Fundamentals
  • 📚 DAMA-DMBOK Aligned Data Governance
  • 🚀 Career Transition Support

Course Curriculum

Module 1 – Foundations of Data Analytics

8 Hours

Topics Covered

  • Understanding Data & Business Processes
  • Data as a Strategic Enterprise Asset
  • Introduction to Data Analytics
  • Data Management Lifecycle
  • Business Problem Solving
  • Types of Analytics
  • Data-Driven Decision Making
  • Industry Use Cases

Module 2 – Master SQL Server

30 Hours

Topics Covered

  • SQL Fundamentals
  • Where clause
  • Joins
  • Aggregate Functions
  • Window Functions
  • Views
  • Stored Procedures
  • Functions
  • Ranking
  • Query Performance Optimization
  • Real Business Scenarios
  • SQL for Data Analytics

Module 3 – Advanced Excel for Analytics

8 Hours

Topics Covered

  • Advanced Formulas
  • Pivot Tables
  • Power Query
  • Data Cleaning
  • Dashboards
  • Lookup Functions
  • What-if Analysis
  • Excel Automation Basics

Module 4 – Mini ETL Project

6 Hours

Topics Covered

  • Data Collection
  • Data Cleaning
  • Data Transformation
  • Data Validation
  • Business Reporting

Module 5 – Tableau Data Visualization

8 Hours

Topics Covered

  • Tableau Desktop
  • Interactive Dashboards
  • Storytelling with Data
  • Filters
  • Parameters
  • LOD Expressions
  • Dashboard Design
  • Executive Reporting

Module 6 – Python for Data Analytics

10 Hours

Topics Covered

  • Python Fundamentals
  • NumPy
  • Pandas
  • Data Cleaning
  • Data Manipulation
  • Exploratory Data Analysis
  • Data Visualization
  • Automation Basics

Module 7 – Enterprise Capstone Project

8 Hours

Develop an end-to-end business solution using:

  • SQL
  • Excel
  • Python
  • Tableau
  • Business Analytics
  • Executive Presentation

Module 8 – Enterprise Data Governance & Data Quality

32 Hours

Topics Covered

  • Data Governance Fundamentals
  • DAMA-DMBOK Framework
  • Data Stewardship
  • Data Ownership
  • Business Glossary
  • Metadata Management
  • Data Catalog
  • Data Quality
  • Data Lineage
  • Master Data Management
  • Governance Operating Model

Module 9 – Cloud & AI for Data Professionals

10 Hours

Topics Covered

  • Cloud Computing Fundamentals
  • Microsoft Azure Fundamentals
  • Databricks Overview
  • Unity Catalog
  • AI Fundamentals
  • AI in Data Governance
  • JIRA Fundamentals
  • Enterprise Data Governance Tools Overview

Module 10 – Career Transition Program

12 Hours

Topics Covered

  • Resume Building
  • LinkedIn Branding
  • Technical Interview Preparation
  • HR Interview Preparation
  • Mock Interviews
  • Salary Negotiation
  • Career Planning & Roadmap

Tools & Technologies Covered

Data Analytics

Microsoft SQL Server
Microsoft Excel
Tableau
Python

Enterprise Data Platforms

Databricks
Unity Catalog
Collibra (Overview)

Cloud & Productivity

Microsoft Azure Fundamentals
JIRA

Who Should Join?

  • Fresh Graduates
  • Working Professionals
  • Software Engineers
  • Business Analysts
  • Banking & Financial Services Professionals
  • Any Non Technical
  • Sales & Marketing Professional
  • Reporting Analysts
  • Career Transition Professionals
  • MBA Students

Program Benefits

  • Live Interactive Sessions
  • Hands-on Assignments
  • Enterprise Capstone Project
  • Real-World Case Studies
  • Industry Expert Mentoring
  • Portfolio Development
  • Resume & LinkedIn Enhancement
  • Interview Preparation
  • Career Transition Support
  • Lifetime Resource Access

Learning Outcomes

By the end of this program, participants will be able to:

  • Analyze business data using industry-standard analytical tools.
  • Write advanced SQL queries for enterprise databases.
  • Build interactive dashboards using Tableau.
  • Perform data analysis and automation with Python.
  • Develop professional reports and dashboards using Excel.
  • Apply enterprise Data Governance principles based on DAMA-DMBOK.
  • Understand cloud technologies and AI concepts relevant to modern data professionals.
  • Build a professional analytics portfolio through real-world projects.
  • Prepare confidently for technical interviews and enterprise data roles.

Career Opportunities

Upon successful completion, participants can pursue roles such as:

Data Analyst
Business Analyst
Data Engineer
Data Steward
SQL Developer
Analytics Consultant
Data Governance Analyst
Data Quality Analyst
Metadata Analyst
Data Governance Consultant
AI Analyst
Data Consultant
Data Governance Lead
BI Analyst
Reporting Analyst

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