This module introduces the fundamental concepts of big data, including data scale, storage, and the defining characteristics known as the 3Vs: volume, velocity, and veracity. Learners will explore how big data is transforming business analytics, the opportunities it presents, and the challenges organizations face in managing and leveraging large-scale data. By the end, you will understand how raw data can be converted into valuable knowledge for decision-making.

This module introduces learners to the evolution and application of advanced analytics and dashboards in transforming raw data into actionable business insights. Participants will explore how analytics tools support effective decision-making and examine organizational factors that influence the adoption of data-driven strategies.

This module explores the evolution and significance of decision-making in management, examining both rational and non-rational approaches. Learners will investigate how data analytics, human judgment, and cognitive processes like dual process theory shape managerial decisions. By understanding different decision types and triggers, participants will gain practical insights into effective decision-making in complex organizational settings.

This module examines how analytics and human judgment interact in management decision-making. Learners will explore frameworks for structuring decisions, the roles of data and intuition, and how context influences the use of analytics. By the end, participants will understand how to balance data-driven insights with managerial expertise in various decision scenarios.

This module examines four distinct types of managerial decision-makers, highlighting their unique approaches to data and judgment in organizational contexts. Learners will assess their own decision-making tendencies and explore how these styles influence leadership effectiveness and team dynamics.

This module explores how managers and organizations prepare for data-driven decision-making by examining influences at the team, organizational, industry, and societal levels. Learners will investigate the stages of data analytics adoption, from initial awareness to maturity, and assess the factors that impact decision quality and strategic outcomes.

This module explores how environmental and organizational factors shape management decision-making, emphasizing the impact of big data, analytics, and external influences. Learners will examine different decision styles, types, and strategies for navigating uncertainty in complex environments. Practical scenarios and reflective questions help deepen understanding of effective decision-making in modern organizations.

This module explores the ethical, legal, privacy, and security challenges organizations face when collecting and using data. Learners will examine real-world privacy policies, legal requirements, and best practices for safeguarding data, while considering the broader societal implications of data-driven decision-making.

This module explores the landscape of emerging technologies such as IoT, edge computing, AI, and Web 3.0, highlighting their definitions, practical applications, and influence on organizational decision-making. Learners will gain insights into how these technologies drive change and present new opportunities and challenges for modern businesses. The module also examines the role of data-driven services and deep learning in shaping future technology strategies.