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Practical Data Analysis for SMEs

A hands-on workshop for data-driven decision making. Use the data you already have, supercharged by AI, to make better decisions.

Format
1 day (8 hours, including breaks)
Level
Intermediate
Prerequisite
Course 1: AI & Prompt Engineering for SMEs

Overview

For many SMEs, 'data analysis' sounds like a luxury reserved for large corporations with teams of data scientists. This course shatters that myth. Designed for the business leader, not the statistician, this workshop focuses on unlocking the value hidden in the data you already have. We explore practical, accessible methods for collecting, cleaning, and analyzing business data using tools you already know (like spreadsheets) supercharged with the power of AI. Participants learn how to ask the right questions of their data, use AI to uncover trends and patterns, and create compelling visualizations that tell a story.

Course schedule & modules

  • Module 1 — The Data-Driven SME: the 'good enough' data mindset and where your data goldmine lives
  • Module 2 — Asking the Right Questions: SMART business questions and defining KPIs
  • Module 3 — Data Prep with AI: cleaning a dirty spreadsheet using AI prompts
  • Module 4 — Descriptive analysis: mean, median, mode, outliers, trends, and relationships
  • Module 5 — Visualization: choosing the right chart for the message
  • Module 6 — Critical evaluation: spotting bias and verifying AI-generated insights
  • Module 7 — Build your one-page Business Insights Dashboard

What you'll leave with

  • Define key data concepts: quantitative vs qualitative, correlation vs causation
  • Identify the valuable data sources hiding inside your SME
  • Use AI tools to clean and standardize a simple dataset
  • Perform basic descriptive analysis and craft prompts that summarize key findings
  • Compare visualization types and pick the right one for your message
  • Create a one-page Business Insights Dashboard answering a specific business question

Audience

  • SME business leaders, operations and finance leads, and team members who work with data but want sharper methods.