Workshop 1: Demystifying Data Analytics for Confident Decision-Makers
6 hours (Half-day)
5,500
Target Audience
Senior leaders, managers, nonprofit executives, and small-business owners
Purpose
Empower decision-makers to understand, interpret, and act on data insights without needing a technical background.
Workshop Modules
What You'll Receive
Participant workbook
CRISP-DM template
Sample data-to-decision storyboard
Workshop 2: AI-Enhanced Data Practices: From Curiosity to Clarity
6 hours (Half-day)
5,800
Target Audience
Educators, analysts, entrepreneurs, and innovation teams exploring GenAI tools for analytics acceleration
Purpose
Introduce responsible and effective integration of AI tools (including prompt engineering) into everyday data workflows.
Workshop Modules
What You'll Receive
Prompt-engineering quick reference card
AI-ethics checklist for organizations
Practice dataset and lab guide
Module 1: What Data Analytics Is—and Isn't
1 hour
Define analytics in plain language, debunk myths about technical expertise
Interactive exercise: 'Instinct vs. Evidence'—making a decision with and without data
Module 3: Building a Data-Driven Culture
1 hour
Identify organizational barriers to data adoption, ethical data practices and responsible storytelling
Group discussion: 'What does data-driven mean for us?'
Module 2: The CRISP-DM Framework in Action
1 hour 30 min
Overview of the six stages: Business Understanding → Data Understanding → Preparation → Modeling → Evaluation → Deployment
Case example: turning business questions into actionable insights
Module 4: From Data to Story
1 hour 30 min
Visual storytelling principles, choosing metrics that matter
Hands-on: sketch a dashboard layout or narrative from sample data
Module 1: The New Data Mindset
1.5 hours
How AI transforms data analysis, understanding data literacy in the age of automation
Interactive poll: 'Where are we on the data confidence spectrum?'
Module 3: Ethics, Bias, and Accountability
1.5 hours
Bias in AI-driven analytics, data privacy and transparency principles
Case reflection: when automation misleads decision-makers
Module 2: Prompt Engineering for Analytics
1.5 hours
Writing effective prompts to clean, summarize, and visualize data
Demonstration: using ChatGPT or Copilot for analytical reasoning
Module 4: Hands-On Mini-Lab
1.5 hours
Experiment with a guided dataset (e.g., sales or community impact)
Peer review of findings through short 'data story' presentations