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Introduction to Business Analytics: Communicating with Data

University of Illinois at Urbana-Champaign via Coursera

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

15 hours 30 minutes
Sessions

Self-Paced
Level

Beginner
Subtitles

Arabic, French, Portuguese, Italian, German, Russian, English, Spanish, Thai, Indonesian, Kazakh, Hindi, Swedish, Korean, Greek, Chinese, Ukrainian, Japanese, Polish, Dutch, Turkish, Hungarian, Bengali, Pashto, Urdu, Azerbaijani, Farsi

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Overview

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This course introduces students to the science of business analytics while casting a keen eye toward the artful use of numbers found in the digital space. The goal is to provide businesses and managers with the foundation needed to apply data analytics to real-world challenges they confront daily in their professional lives. Students will learn to identify the ideal analytic tool for their specific needs; understand valid and reliable methods for collecting, analyzing, and visualizing data; and utilize data to inform decision-making for their agencies, organizations, or clients. The course also examines the rapidly evolving role of artificial intelligence in analytics, with a focus on using AI as a drafting partner while keeping human judgment and accountability firmly in the loop.

Syllabus

Course Introduction and Module 1: Structuring Insights: Data Storytelling Foundations and Frameworks

This module establishes that effective communication with data begins with storytelling, not visualization. You will learn why a clear story is more durable than any specific tool, and you will be introduced to the structured frameworks that consultants, executives, and analysts use to organize insight.

Module 2: Gaining Insights from Data: Exploration, Visualization, and Iteration

This module shifts from structure and storytelling to the process of generating insights from data itself. You will learn how people perceive visual information, which encodings communicate most accurately, how to move from raw data to audience-ready visuals through exploration and iteration, and how to navigate the modern data visualization tool landscape.

Module 3: Extending Insights: Visualizing Unstructured and Complex Data

Modern analytics increasingly involves data that does not fit neatly into rows and columns, including text, location, images, and high-dimensional behavioral signals. This module introduces practical frameworks for visualizing these data types and emphasizes that complex data demands more clarity, not more visual complexity.

Module 4: Working with AI: Drafting Visuals and Communicating for Responsible Decision-Making

This module examines what changes, and what doesn't, when AI enters the analytics workflow. Rather than treating AI as a black box that produces final answers, you will learn to use AI as a fast drafting partner while keeping human framing, evaluation, and accountability firmly in the loop. The module also examines what happens when AI-generated visualizations operate at scale and what governance and disclosure practices are demanded.