Business analytics involves using data analysis to drive decision-making in business. This section introduces the field’s importance, covering descriptive, predictive, and prescriptive analytics, along with essential tools and techniques.

This section focuses on ensuring data quality and readiness for analysis. It covers data collection methods, cleaning, preprocessing, and visualization techniques to address issues like missing data and outliers.

Statistical analysis is crucial for uncovering insights from data. Participants learn basic statistical concepts and predictive modeling techniques such as regression and classification for forecasting and decision-making.

Here, participants explore business intelligence tools and data mining techniques to uncover patterns and insights from data, including association rule mining, clustering, and sentiment analysis.

Decision support systems and optimization techniques are discussed, focusing on resource allocation, linear programming, simulation modeling, and the challenges of implementing analytics solutions.