Management Decision-Making, Big Data and Analytics

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

10 weeks, 1 hour a week
Sessions

Self-Paced
Level

Beginner
Subtitles

English

Found in

Overview

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This course explores the role of big data and analytics in shaping management decisions, highlighting key models, tools, and organisational factors. It demonstrates how data-driven strategies support informed choices in modern professional environments. Learners will gain practical skills to leverage analytics for effective decision-making, integrating data insights with human judgment and organisational context. The course emphasizes real-world applications, ethical considerations, and frameworks that enhance analytical thinking. Combining theory with applied examples, this course uniquely bridges managerial decision-making with big data practices, ensuring learners can translate insights into actionable outcomes. Ideal for managers, business analysts, and professionals aiming to strengthen data-informed decision-making, with a basic understanding of organisational concepts recommended. This course is based on the book, Management Decision-Making, Big Data and Analytics, by Simone Gressel, David Pauleen, Nazim Taskin. Copyright ©2021 by Sage Publications Limited. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies. Published by Sage Publications Limited, London. Used by arrangement with Sage Publications Limited.

Syllabus

Professional Mindsets

This module explores the contrasting mindsets of managers and information technologists, highlighting how these differences impact communication and collaboration in organizations leveraging big data. Learners will discover strategies for building shared mental models and addressing talent shortages to enhance team performance.

Introduction to Big Data

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.

Introduction to (Advanced) Analytics

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.

Management Decision-Making

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.

Analytics in Management Decision-Making

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.

Types of Managerial Decision-Makers

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.

Organisational Readiness for Data-Driven Decision-Making

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.

Integrating Contextual Factors in Decision-Making

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.

Managing the Ethics, Security, Privacy and Legal Aspects of Data-Driven Decision-Making

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.

Managing Emerging Technologies and 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.