AI for Data Analysis and Report Writing
A practical eight-hour programme for people who have to turn numbers into a written report, built for participants with little or no prior AI experience. The day starts from scratch with what AI and generative AI actually are, moves through prompting that reliably works, and then spends the second half on the two tasks that consume the most time in most offices: making sense of data, and writing it up. Participants finish by taking a real dataset all the way through to a completed short report.
Programme Agenda
Part 1: Introduction to AI and Generative AI
What AI and Generative AI Actually Are
A plain-language explanation with no mathematics and no jargon. What a large language model is doing when it writes, and why that explains both its strengths and its failures. A guided tour of the three tools most Malaysian organisations already have access to: ChatGPT, Google Gemini and Microsoft Copilot. What each one is genuinely better at, and how to work out which is already licensed at your workplace.
What AI Can and Cannot Do
The honest capability boundary, drawn with examples rather than warnings. Hallucinations: why a model invents a confident, wrong answer, what that looks like in practice, and the verification habits that catch it before it reaches your manager. Confidentiality and what should never be pasted into a public tool. Where accountability stays with the human no matter what the tool produced.
Part 2: Prompt Engineering
Giving Clear and Effective Instructions
The anatomy of a prompt that works: role, task, context, output format and constraints. Why vague questions produce vague answers, and how a few extra sentences of context change the result entirely. Working through weak prompts and rewriting them live so participants can see the difference in the output rather than take it on trust.
Structuring Prompts and Practical Exercises
Hands-on prompting clinic using participants' own recurring work tasks. Iterating on a response instead of accepting the first draft, asking the model to critique its own output, and using examples to lock in the format you want. Participants start building a personal prompt library they keep after the training.
Part 3: AI for Data Analysis
Understanding and Analysing Data with AI
Working with a spreadsheet directly in an AI tool. Cleaning and structuring messy data before analysis, which is where most attempts quietly fail. Asking questions that produce useful answers: summaries, comparisons, trends over time, and outliers worth investigating. Critically, how to check the arithmetic, because data work is where AI is most likely to be confidently wrong.
Identifying Insights, Trends and Key Findings
Moving from what the data says to what it means. Using AI to surface patterns you might not have looked for, then testing whether they hold up. Separating a genuine finding from a coincidence. Turning each finding into a plain-language statement that a non-analyst can read once and act on.
Part 4: AI-Assisted Report Writing
Structuring and Drafting Reports
Getting a usable outline before writing a single paragraph, and why this single step saves the most time. Drafting sections from your findings, summarising long source documents without losing the important qualifications, and writing an executive summary that genuinely summarises rather than restating the introduction.
Improving Clarity and Presentation
Editing AI output so it does not read like AI output: cutting padding, fixing the repetitive rhythm, and restoring your organisation's tone. Adjusting the same report for different readers, from an operational team to a board. Practical formatting for readability.
End-to-End Exercise
The final session puts the whole day together. Participants take a raw dataset through cleaning, analysis, findings and drafting to a finished short report in one sitting, using their own prompt library. This is the session that converts a day of demonstrations into a workflow people actually repeat on Monday.
Who Should Attend:
Executives, officers and managers who prepare reports from data as part of their role. Finance, operations, HR, marketing and administrative staff who work with spreadsheets and written reporting. Government and GLC staff producing periodic reports and submissions. Anyone with limited or no prior AI experience who has been told to start using it and does not know where to begin. No technical or programming background is required.
Key Outcomes:
Explain in plain language what generative AI is and where its limits are
Choose confidently between ChatGPT, Gemini and Copilot for a given task
Recognise hallucinations and apply a verification routine before using AI output
Write structured prompts that produce usable results on the first or second attempt
Prepare and analyse a dataset with AI, including checking its arithmetic
Turn raw data into clear findings a non-analyst can act on
Draft, summarise and edit a report with AI assistance
Leave with a personal prompt library and a completed sample report
Duration: 1 Day (8 Hours), splittable across two half days
Training Hours: 9:00 AM to 5:00 PM, or a schedule you set
Level: Beginner / All levels / Non-technical
Training Mode: Physical, Online, or Hybrid
HRD Corp SBL-KHAS Claimable
Certificate of Completion included