About the Program
Business Analytics, tailored for IT graduates, is a dynamic discipline centered on harnessing data and advanced statistical methodologies to tackle intricate business challenges. At the heart of this field lies the ability to transform raw data into actionable insights, empowering strategic decision-making within organizations. Business analysts, equipped with their analytical acumen, assume a pivotal role in enhancing operational efficiency, accurately forecasting trends, and ultimately, driving profitability through the implementation of data-driven strategies. This specialized skill set positions them as catalysts for growth and innovation in organizations across the business spectrum.
Courses
    Credits Semester
  • Fundamentals of Business Analytics 3 III
  • Statistics for Business Analytics 3 IV
  • Tools for Business Analytics 3 V
  • Applied Business Analytics 3 V
  • Predictive Modelling 3 VI
  • Data Driven Storytelling and Visualization 3 VII
  • Project Work - The Business Analytics Capstone: Exploring Data Insights for Business Decisions 3 VIII
    Credits Semester
  • IT World Essentials: Your Digital Entrypoint 3 I
  • Critical Thinking, Design Thinking, Leadership and Teamwork 3 II
  • Project Work - The Business Analytics Capstone: Exploring Data Insights for Business Decisions 3 VIII
    Credits Semester
  • Critical Thinking, Design Thinking, Leadership and Teamwork 3 II
  • Career Readiness in Digital Era 3 VI
Mode of Delivery
  • Self-paced learning – 10 hours
  • VILT sessions – 28 hours
  • Project work – 7 hours
  • Face-to-face instructor led sessions / VILT sessions (including project work) – 45 hours
  • Self-paced learning + Expert session – 30 hours
  • Project work – 15 hours
Job Roles
  • Analytics Manager
  • Business Systems Analyst
  • Business Analyst
  • Data Analyst
  • Business Intelligence
Software Tools
  • Microsoft Excel
  • Tableau
  • Statistical Software Suite (SAS)
  • Microsoft Power BI
  • Python
  • R
Skills
  • Applying advanced statistical analysis techniques for actionable business insights and decisions.
  • Utilizing business intelligence tools like Power BI and Tableau for informed decision-making.
  • Performing exploratory data analysis (EDA) for uncovering business trends and patterns.
  • Implementing predictive analytics and machine learning models for future forecasting and planning.
  • Designing ETL (Extract, Transform, Load) processes for efficient business data integration.
  • Communicating valuable business insights through clear and effective data storytelling methods.