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Nielsen Norman Group

UX Data in Spreadsheets: Cleaning and Organizing

via Nielsen Norman Group

Overview

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Ensure your UX data is clean, structured, and analysis-ready using essential spreadsheet techniques. Save time with high-efficiency data cleaning techniques. Protect data while cleaning it. Evaluate and improve data quality.

Syllabus

Course Curriculum

Introduction (3 Lessons, 19 min)

  • Course Overview & Downloads
  • What Is Messy Data?
  • Common Types of UX Spreadsheet Data

Top 3 Priorities While Cleaning Data (4 Lessons, 23 min)

  • Privacy and Security
  • Documentation: Why It's Important
  • Documentation: How to Document Effectively
  • Efficiency

Missingness (6 Lessons, 65 min)

  • Missingness: Importance of Identifying
  • Missingness: Causes (Part 1)
  • Missingness: Causes (Part 2)
  • Missingness: How to Identify (Part 1)
  • Missingness: How to Identify (Part 2)
  • Missingness: Listwise Deletion

Duplicates (5 Lessons, 61 min)

  • Duplicates: Importance of Identifying
  • Duplicates: Causes
  • Duplicates: Key Variables
  • Duplicates: How to Identify
  • Duplicates: Deciding Which to Keep

Inconsistent Formatting (2 Lessons, 18 min)

  • Inconsistent Formatting: Common Issues
  • Inconsistent Formatting: Find and Replace

Incorrect Data Types (1 Lesson, 24 min)

  • Fixing Incorrect Data Types

Exploratory Data Analyses (7 Lessons, 77 min)

  • Why are Exploratory Data Analyses Important?
  • Descriptive Statistics (Part 1)
  • Descriptive Statistics (Part 2)
  • Pivot Tables
  • Basic Data Visualizations
  • When to Use Which Exploratory Data Analysis Method
  • Final Thoughts

Taught by

Rachel Banawa

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