# Data Storytelling with Excel (Self-Paced)

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

## Overview

Data alone does not drive decisions; stories do. In this hands-on course, you will learn how to transform raw data into clear, compelling visual narratives using Microsoft Excel. You will work through a complete storytelling process, including understanding your audience, choosing the right visualization, eliminating clutter, focusing attention, and delivering insights that move people to action.

Grounded in cognitive science and design thinking principles, this course goes beyond simply showing you how to make a chart by helping you understand why some visualizations work and others fail. Through real-world examples and practical exercises, you will build the skills to communicate complex information with clarity, credibility, and impact, whether you are presenting to executives, colleagues, clients, or broader audiences.

## What you'll learn

- Apply a structured framework to define context, audience, and narrative goals before creating a visualization
- Select the most effective chart type based on data relationships and intended message
- Recognize and eliminate visual clutter that obscures meaning
- Use preattentive attributes and Gestalt principles to direct audience attention
- Think like a designer to create accessible, polished, and intuitive visualizations
- Build a data-driven narrative using proven storytelling techniques
- Avoid common visualization mistakes and ethical pitfalls
- 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