Introduction to Business Analytics

This module provides a foundational overview of business analytics principles and practices. It explores key concepts in data analytics, establishing a common vocabulary and conceptual framework for understanding how organizations leverage data for business value. The module examines different categories of data analytics, including descriptive, diagnostic, predictive, and prescriptive approaches, explaining their distinct purposes and business applications. It covers the analytics lifecycle from data acquisition and preparation through analysis and implementation, highlighting the iterative nature of analytics projects. The module concludes with a case study of Alpina's data analytics model, demonstrating how a leading food company has integrated analytics into its business operations to drive innovation and competitive advantage.

Skills you'll gain

This module focuses on data management practices as the foundation for effective business analytics. It examines approaches to data administration, including data governance frameworks, quality assurance processes, and security protocols that ensure data integrity and compliance. The module explores data modeling techniques that transform raw information into structured formats optimized for analysis, covering relational models, dimensional modeling, and emerging approaches for unstructured data. It concludes with a practical examination of Alpina's data management practices, demonstrating how the company has implemented data governance policies, quality management systems, and integration technologies to create a robust foundation for its analytics initiatives.

Skills you'll gain

This module examines analytical modeling approaches and their application in business decision-making. It explores the paradigms and limitations of different modeling techniques, helping learners understand the appropriate contexts for various analytical methods and their constraints. The module covers modeling methodologies across the analytics spectrum, from statistical analysis and data mining to machine learning and optimization algorithms, explaining how each approach addresses different business questions. It concludes with an examination of Alpina's analytics applications, showcasing real-world examples of how the company has implemented various modeling techniques to solve specific business challenges, such as demand forecasting, customer segmentation, and product optimization.

Skills you'll gain

This module focuses on data visualization and communication methods for translating analytical insights into business action. It examines various presentation techniques for analytical results, including dashboard design, interactive visualizations, and narrative approaches that effectively communicate findings to different stakeholders. The module explores how visualization choices impact understanding and decision-making, covering principles of visual perception, chart selection, and storytelling with data. It concludes with an examination of Alpina's data presentation practices, demonstrating how the company transforms complex analytical results into accessible insights that drive business decisions across different organizational levels, from operational teams to executive leadership.

Skills you'll gain