
AI+ Data Analysis
Make Sense of Any Dataset, Fast
Data to insight, fast — without the AI hallucination trap.
You have the data. You open the spreadsheet, scroll for a few minutes, and still aren't sure what it's telling you. The gap isn't data literacy — it's a structured process for what to do before, during, and after AI analysis. This book gives you the 36-prompt Data Analysis Prompt Toolkit, the TRUST framework applied to data contexts, and a 30-day starter plan. Built by an AI engineering firm for analysts who know the numbers don't speak for themselves.
Inside
- 36 ready-made, market-tested prompts: question framing, dataset assessment, exploratory analysis, pattern identification, chart selection, insight communication
- The TRUST Framework applied to data contexts — checking AI analysis for accuracy before any of it reaches a stakeholder
- A "frame the question" workflow that connects data to a real decision before any analysis begins
- A communication discipline that puts the recommendation where it lands, not where it's buried
- A 30-day plan for marketers, operations managers, finance professionals, researchers, policy analysts, and project managers working with data daily
Who this is for
Any professional who regularly handles data but does not call themselves a data analyst: a marketer reviewing campaign performance, a researcher processing survey results, a finance professional analysing budget variances, an operations manager tracking KPIs, a policy analyst interpreting statistics, a project manager reviewing delivery metrics. The book is cross-industry by design — the skill is the same whether the dataset is a sales export, a patient survey, or a grant application tracker.
Also for:Junior data analysts and data-adjacent professionals (BI report users, dashboard owners) who want to work faster and more confidently with AI assistance.
You’ll be able to
- Frame a clear analytical question that connects data to a real decision
- Assess the structure, type, and quality of a dataset before starting analysis
- Use AI to explore, describe, and find patterns in data
- Apply the TRUST framework to critically evaluate AI-generated analysis and detect errors
- Select the right visualisation for a given finding
- Communicate data insights to non-technical audiences using AI-assisted narratives
What’s inside
- Diagnostic
- How AI-ready is your data analysis?
- Chapter 1
- AI in Data Analysis Right Now
- Chapter 2
- Before You Touch the Data: Asking the Right Question
- Chapter 3
- Understanding What You Have
- Chapter 4
- Cleaning and Preparing Your Data
- Chapter 5
- Exploring and Describing Your Data
- Chapter 6
- Finding Patterns and Relationships
- Chapter 7
- Interpreting AI-Generated Analysis
- Chapter 8
- Choosing the Right Visualisation
- Chapter 9
- Communicating Findings to Non-Technical Audiences
- Chapter 10
- Your 30-Day Data Analysis Starter Plan
- Back matter
- Skill Summary · Recommended Next Reads · Glossary · Tool Reference
How can AI help with data analysis?
AI for data analysis assesses a dataset, explores it, finds patterns and suggests charts once you've framed the question. Check its analysis for accuracy before any of it reaches a stakeholder.
AI+ Data Analysis gives you 36 ready-made prompts and the TRUST Framework applied to data contexts.
Built by an AI engineering firm — for analysts who know the numbers don't speak for themselves.
Part of these packs
Appears in 7 reading paths
Reads well with
Often read alongside this title.
T3-95 · Job SkillsAI+ Monitoring & Evaluation
T3-80 · Job SkillsAI+ Data Storytelling
T3-84 · Job SkillsAI+ Quantitative Research & Statistics
T3-01 · Job SkillsAI+ Academic Research
T3-83 · Job SkillsAI+ Systematic Literature Reviews
T3-85 · Job SkillsAI+ Laboratory Research & Experimental Design
T3-82 · Job SkillsAI+ Qualitative Research Methods
T3-86 · Job SkillsAI+ Fieldwork & Ethnographic Research
