# Data Storytelling with Excel (Self-Paced)

Canonical URL: <https://www.creativelive.com/classes/data-storytelling-with-excel-self-paced>

## Overview

Data becomes more useful when it is presented as a clear story. In this hands-on course, students learn how to transform raw data into compelling visual narratives using Microsoft Excel. The course covers a complete storytelling workflow, including understanding your audience, selecting the right visualization, reducing clutter, directing attention, and presenting insights in a clear and persuasive way.

Built on principles of cognitive science and visual design, this course goes beyond basic chart creation to explain why some visualizations communicate effectively while others do not. Through practical exercises and real-world examples, learners develop the skills to present complex information with clarity, credibility, and impact for a variety of audiences and settings.

## What you'll learn

- Apply a structured framework to define context, audience, and narrative goals before creating any visualization
- Select the most effective chart type based on data relationships and intended message
- Recognize and eliminate visual clutter that obscures your data's meaning
- Apply preattentive attributes and Gestalt principles to direct audience attention
- Think like a designer to create accessible, aesthetic, and intuitive visualizations
- Structure a data-driven narrative using proven storytelling techniques
- Avoid common visualization mistakes and ethical pitfalls
- Confidently present data stories that inform, persuade, and inspire action

## Curriculum

#### Module 1: Foundations — Data, Stories, and Audience

- Identify what makes a data story work and distinguish data from information
- Recognize internal and external data sources and understand how data flows across the internet
- Apply audience analysis and learning style awareness to tailor your data story

#### Module 2: Reading and Perceiving Visualizations

- Interpret a range of chart types including bar, heat map, KPI, stacked, and drilldown visualizations
- Apply visual perception principles — order, hierarchy, clarity, and convention — to evaluate any chart
- Use Gestalt principles, emphasis, and annotation to guide audience attention

#### Module 3: Building Effective Visualizations

- Select the appropriate visualization type for comparative, time series, correlation, and geographic data
- Use color intentionally and avoid common deceptive chart techniques
- Follow a step-by-step process for building a data story using the analytics value chain

#### Module 4: Excel for Data Discovery and Analysis

- Perform data discovery and integrity checks to qualify data before analysis
- Use AutoSum, sorting, filtering, and math functions to explore datasets
- Build Pivot Tables and Pivot Charts to summarize and visualize transactional data

#### Module 5: AI, Data Quality, and Applied Case Studies

- Use AI tools and prompting best practices to confirm and refine a data story
- Apply data quality principles and joining techniques to prepare datasets for analysis
- Complete hands-on case studies covering duplicate analysis, stratification, Benford's Law, sampling, and analysis automation

## Pricing

**Tuition:** $399