Business Analytics: Data Analysis for Decisions

via Coursera

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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 provides business professionals with essential knowledge in data analysis to support informed decision-making. Understanding how analytics informs marketing, HR, operations, and financial strategies is key to enhancing organizational performance and competitiveness. The course helps learners develop the skills needed to apply analytical methods to real-world business problems. Through practical exercises and case studies, participants learn to interpret data, communicate insights, and make decisions that drive measurable outcomes. What sets this course apart is its combination of theory and real-world applications, blending analytical techniques with business strategy. Learners gain hands-on experience with data, ensuring insights are actionable and aligned with organizational objectives. Designed for managers, business analysts, and professionals in leadership or decision-making roles, this course assumes basic familiarity with business concepts. It is ideal for those seeking to strengthen their ability to translate data into strategic action. This course is based on the book, Business Analytics: Combining Data Analysis and Judgement to Inform Decisions, by Mary Ellen Gordon. Copyright ©2023 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

How Data and Analytics Can Enhance Human Decision-Making in Organisations

This module introduces the fundamentals of business analytics and their role in supporting organisational decision-making. Learners will explore the interplay between data analysis and human judgment, and understand the importance of distinguishing between populations and samples when interpreting data. Practical considerations for planning analytics projects within organisational constraints are also discussed.

Why Organisational, Legal, Cultural, and Ethical Considerations Shape What Can and Should be Done With Data and Analytics

This module explores how organisational structures, legal frameworks, cultural norms, and ethical principles shape data practices and decision-making. Learners will gain insight into key regulations like GDPR, the importance of cultural awareness, and frameworks for ethical data use. Practical examples and guidelines help clarify what is permissible and responsible when working with data.

Preparing to Work With Data

This module introduces the foundational steps for working with organizational data, including identifying data sources, understanding data structures, and applying essential cleaning techniques. Learners will explore how to classify variables, handle missing or problematic data, and prepare datasets for effective analysis and visualization.

Analysis Fundamentals

This module introduces key analytical techniques for quantifying qualitative data, performing statistical tests, and making data-driven decisions using Excel. Learners will explore how to answer different types of business questions, interpret statistical significance, and apply regression analysis for prediction. Practical Excel skills are emphasized throughout to ensure hands-on experience with real-world data analysis.

Communicating Analytical Results

This module guides learners in effectively communicating analytical results by considering audience knowledge, project objectives, and data visualization best practices. You will explore how to select and design impactful visualizations, craft clear narratives, and evaluate the effectiveness of your data-driven communications.

Marketing Analytics

This module introduces the use of analytics in marketing, focusing on how data-driven insights inform decisions about market opportunities, customer segmentation, pricing, distribution, and communication strategies. Learners will explore practical applications of analytics to optimize marketing effectiveness and address common challenges in data collection and interpretation.

HR/People Analytics

This module introduces the use of data analytics in human resources to measure employee performance, monitor diversity and inclusion, assess training effectiveness, and support talent acquisition. Learners will discover how data-driven insights can inform equitable and effective HR practices. Practical examples and common data sources are explored to help you understand real-world applications.

Operational Analytics

This module explores how organizations leverage analytics to optimize supply chain management, enhance sustainability, implement predictive maintenance, and detect fraud. Learners will gain insights into key data sources, analysis techniques, and ethical considerations relevant to operational analytics. Practical examples illustrate how analytics can be tailored to diverse organizational needs.

Financial Analytics

This module explores how data analytics can inform financial decision-making across marketing, HR, and operations. Learners will discover how to assess the financial impact of organizational activities, evaluate overall financial health, and apply analytical techniques to real-world business scenarios. Practical examples and case studies illustrate how analytics can drive more informed, data-driven financial strategies.

The Future of Data and Analytics

Explore how emerging technologies like IoT, AR, VR, AI, and edge computing are transforming the landscape of data analytics. Learn about the implications for privacy, data processing, and new career opportunities in this evolving field.