AI-Powered Data Analysis, Reporting & Storytelling

Introduction

This programme equips participants with the skills to use AI tools (NotebookLM and Google Gemini) to transform data and documents into meaningful insights, clear reports, and sound business decisions. Participants will learn how to think analytically, recognise patterns, and avoid common data interpretation pitfalls before applying AI to real-world analysis and reporting tasks.

The course emphasises using AI as a research assistant, analyst, and decision support tool, while maintaining human judgment, governance, and accountability. Through structured frameworks and practical examples, participants will gain confidence in producing credible, executive-ready, and decision-oriented outputs using AI responsibly.

Tools/Technologies Required

• NotebookLM
• Google Gemini

Learning Outcomes

By the end of this course, participants will be able to:

• Apply a data-driven mindset to move beyond reporting numbers toward insight and decision making
• Use NotebookLM to extract, validate, and structure insights from documents and written sources
• Use Google Gemini to perform analytical reasoning on datasets, trends, and comparisons
• Produce clear, management-ready reports with actionable insights and recommendations
• Identify AI limitations, risks, and governance considerations when using AI in business contexts

Key Content

Module 1: AI for Business & Decision Intelligence

• Understanding where NotebookLM and Google Gemini fit within data workflows
• Traditional vs AI-assisted data analysis
• When to use AI for different business needs
• Using AI as a research assistant, analyst, and decision support tool

Module 2: Data Mindset & Analytical Thinking

• What it means to think with data instead of just reporting numbers
• DIKW framework: Data → Information → Knowledge → Wisdom
• Common analytical blind spots: assumptions, bias, correlation traps
• How to recognise meaningful patterns: trends, anomalies, outliers, segments

Module 3: Foundations of Insight Generation

• How to spot patterns in raw data: correlations, drop-offs, spikes, differences
• Basic statistical thinking for insights: averages, variance, % change
• Indicators of a strong insight: relevance, context, actionability
• Contrasts, cohorts, control groups
• Basic logic patterns used in data analysis

Module 4: NotebookLM for Document-Based Insight Extraction

• Understanding how NotebookLM differs from chatbots through strict source grounding
• Working with internal documents such as PDFs, reports, SOPs, policies
• Using citations to trace insights back to original documents

Module 5: NotebookLM for Insight Structuring & Narrative Building

• Turning raw answers into structured, decision-ready insights
• Extracting key findings, supporting evidence, assumptions, and gaps
• Using NotebookLM to produce executive summaries, briefing notes, and issue trees

Module 6: Google Gemini for Data Analysis & Analytical Reasoning

• Uploading, reading, and interacting with datasets for analysis
• Asking data-driven analytical questions, including:
  • Trend and pattern analysis
  • Comparisons across categories, time periods, or segments
  • Identifying outliers and anomalies
• Integrating NotebookLM’s document intelligence with Google Gemini’s analytical reasoning

Module 7: AI-Assisted Reporting & Visualization Thinking

• Structuring AI outputs for management reports, steering committee decks, and operational reviews
• Using Gemini to draft report sections, suggest charts and KPIs, and translate analysis into plain business language
• Turning analysis into clear insights, implications, and actionable recommendations

Module 8: Limitations, Risks & Responsible Use of AI

• Understanding AI Limitations
• Common Risks in AI-Assisted Analysis
• Data Privacy, Security & Governance Considerations

Methodology

Presentations/conceptual briefings, guided examples, group activities, case-based learning, hands-on exercises

Target Audience

• Business professionals, managers, and executives who need to communicate insights, performance trends, or analytical findings effectively.
• Anyone seeking to strengthen analytical thinking for data-informed business decisions