Principles of Data Analytics
A practical 5-day training course that helps professionals turn raw data into clear
insights, better decisions, and measurable business value.
Ideal for managers, analysts, supervisors and professionals who work with reports,
dashboards, or performance metrics.
Course Overview
The Principles of Data Analytics course builds a solid foundation in how to think
analytically, how to structure data-driven questions, and how to use data responsibly to
support decisions in the workplace.
Rather than focusing only on tools and formulas, the programme emphasises mindset,
thinking frameworks, practical examples and real-world decision scenarios.
By the end of the course, participants will be able to confidently read, question and use
data in their day-to-day roles.
What You Will Learn
- Understand the core concepts and language of data analytics.
- Frame strong analytical questions that can actually be answered with data.
- Differentiate between data, information, insight, and action.
- Apply analytical thinking to real workplace problems and decisions.
- Recognise common data pitfalls, biases, and “bad” analysis.
- Use data ethically and responsibly, respecting privacy and context.
- Design simple measurement frameworks and KPIs to track performance.
- Communicate insights clearly through storytelling, visuals, and recommendations.
- Managers and supervisors who receive reports and dashboards.
- Business professionals who support decisions with data.
- New or aspiring data analysts / MIS officers.
- Project leads, M&E officers and team leaders.
- Anyone who wants to become more confident with data-driven thinking.
Course Structure – 5 Day Programme
The training is organised over five interconnected days. Each day combines short
inputs from the facilitator, guided discussions, practical exercises, and reflection on
participants’ own work situations.
Day 1 – Foundations of Data Analytics & Analytical Mindset
- What is data analytics? Key terms, concepts, and levels of analytics.
- Data vs information vs insight vs action.
- Characteristics of good data and good questions.
- Developing an analytical mindset in everyday work.
- Group exercises using simple datasets and business scenarios.
Day 2 – Applying Analytical Thinking to Workplace Decisions
- Translating vague problems into strong analytical questions.
- Linking data to business objectives, KPIs, and decision points.
- Basic techniques for exploring and interpreting data patterns.
- Case work: customer complaints, budget variances, operational performance.
- Peer review of analytical questions and assumptions.
Day 3 – Ethical, Responsible, and Influential Analytics
- Ethics in data analytics: privacy, consent, fairness, and transparency.
- Recognising bias, misuse of statistics, and misleading visuals.
- Balancing analytical rigour with real-world constraints.
- Positioning insights so they influence decisions, not just inform.
- Role-plays: pushing back on “data abuse” and unrealistic requests.
Day 4 – Monitoring, Measuring, and Storytelling for Improvement
- Designing simple measurement frameworks and indicators.
- Choosing the right metrics and avoiding “vanity” indicators.
- Turning analysis into a clear narrative: context, insight, implication, action.
- Basics of visual storytelling using tables, charts, and dashboards.
- Mini-presentations: participants present short data stories.
Day 5 – Applied Decision Analytics & Integration Workshop
- Group project: end-to-end analysis of a realistic business scenario.
- Framing the question, selecting data, exploring patterns, drawing insights.
- Developing recommendations and implementation considerations.
- Designing a basic monitoring plan to track results over time.
- Action planning: how participants will apply what they learned at work.
Training Methodology
The course is highly interactive and practical. We use:
- Short conceptual inputs to build a shared language.
- Practical exercises using realistic datasets and scenarios.
- Group work, peer learning, and guided discussions.
- Role-plays and case studies focused on workplace decisions.
- Reflection activities to link insights back to each participant’s role.
The emphasis is not on complex statistics, but on thinking clearly with data,
asking better questions, and using evidence to support practical decisions.
Course Logistics
- Format: Face-to-face workshop / Virtual (depending on arrangement)
- Duration: 5 days (approx. 6 learning hours per day)
- Delivery: Facilitator-led, with hands-on exercises
- Materials: Participant manual, slide deck, templates & case studies
- Class size: Recommended 12–25 participants
Registration & Enquiries
For dates, fees, and in-house delivery options, please contact us:
- Email: Email Us to book
- Phone: +263 719 397 464
You can also request a customised version of this course using your own
organisation’s data, reports, and decision scenarios.
Contact Us to Book
15 George Silundika Avenue,
Email: info@dataanalysis.co.zw
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