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Mai Studies Original · Data & Analytics

Data Analytics & Business Intelligence

An eight-week professional programme covering data quality, SQL, Python, statistics, visualisation, dashboard design, governance and analytical communication. Learners build a portfolio-ready intelligence product from an original business case.

8 weeks 48 guided hours Intermediate
Join membership to study

Included with Mai Studies membership at no extra cost. Fee waivers are available through scholarships and open access.

Data Analytics & Business Intelligence course artwork

What you will achieve

  • Design a reliable analytical workflow
  • Query and transform relational data with SQL
  • Analyse and visualise data with Python
  • Build governed dashboards and communicate decisions

Entry guidance

  • — Comfort with spreadsheets
  • — Basic numeracy
  • — No prior programming experience required

Original Mai Studies learning material. This is a professional completion programme, not a regulated qualification or university accreditation.

Programme syllabus

8 applied modules

Lessons
16
Assessed tasks
8
Practice questions
96
Timed mock papers
2
01

Analytical questions and data quality

Define decision questions, measures, grain, ownership and quality expectations.

2 lessons · 12 practice questions · 1 assessed task

  1. 1. From decision to analytical question37 min study · 2 learning objectives · practical activity

    Convert stakeholder needs into measurable analysis.

  2. 2. Data quality and lineage36 min study · 2 learning objectives · practical activity

    Trace evidence from source to decision.

  • Module 1 applied brief — marked out of 100, pass at 80%
02

Spreadsheet controls and relational thinking

Build controlled calculations and translate tabular work into relational structures.

2 lessons · 12 practice questions · 1 assessed task

  1. 1. Controlled spreadsheet analysis37 min study · 2 learning objectives · practical activity

    Make spreadsheet work reviewable and repeatable.

  2. 2. Relational models and dimensional design40 min study · 2 learning objectives · practical activity

    Organise data for consistent analysis.

  • Module 2 applied brief — marked out of 100, pass at 80%
03

SQL for trustworthy analysis

Query, join, aggregate and validate relational data without losing business meaning.

2 lessons · 12 practice questions · 1 assessed task

  1. 1. SQL selection, joins and aggregation40 min study · 2 learning objectives · practical activity

    Write queries that preserve business meaning.

  2. 2. Windows, dates and analytical SQL37 min study · 2 learning objectives · practical activity

    Answer ranking and trend questions reproducibly.

  • Module 3 applied brief — marked out of 100, pass at 80%
04

Python analytical workflows

Create reproducible cleaning, exploration and transformation workflows.

2 lessons · 12 practice questions · 1 assessed task

  1. 1. Python data preparation37 min study · 2 learning objectives · practical activity

    Build an auditable analytical notebook or script.

  2. 2. Exploration without self-deception38 min study · 2 learning objectives · practical activity

    Find patterns while controlling analytical bias.

  • Module 4 applied brief — marked out of 100, pass at 80%
05

Statistics for decisions

Use uncertainty, sampling and practical significance to challenge conclusions.

2 lessons · 12 practice questions · 1 assessed task

  1. 1. Uncertainty, sampling and practical significance37 min study · 2 learning objectives · practical activity

    Quantify how confident a decision should be.

  2. 2. Experiments and causal caution37 min study · 2 learning objectives · practical activity

    Avoid turning association into unsupported cause.

  • Module 5 applied brief — marked out of 100, pass at 80%
06

Visualisation and data storytelling

Choose honest visual encodings and construct a clear evidence-led narrative.

2 lessons · 12 practice questions · 1 assessed task

  1. 1. Honest visual encoding38 min study · 2 learning objectives · practical activity

    Choose charts that reveal rather than decorate.

  2. 2. Evidence-led storytelling37 min study · 2 learning objectives · practical activity

    Structure analysis for action and challenge.

  • Module 6 applied brief — marked out of 100, pass at 80%
07

Business intelligence design and governance

Design useful metrics, semantic definitions, refresh controls and accessible dashboards.

2 lessons · 12 practice questions · 1 assessed task

  1. 1. Metrics, semantic layers and dashboard design37 min study · 2 learning objectives · practical activity

    Create consistent measures and usable monitoring views.

  2. 2. Refresh, access and BI governance36 min study · 2 learning objectives · practical activity

    Operate intelligence products reliably.

  • Module 7 applied brief — marked out of 100, pass at 80%
08

Analytics portfolio capstone

Deliver a governed intelligence product and executive recommendation.

2 lessons · 12 practice questions · 1 assessed task

  1. 1. Capstone: governed intelligence product42 min study · 2 learning objectives · practical activity

    Integrate data, analysis and dashboard evidence.

  2. 2. Capstone: executive recommendation38 min study · 2 learning objectives · practical activity

    Defend an analytical recommendation responsibly.

  • Final applied project — marked out of 100, pass at 80%

Timed mock papers

  • Data Analytics & Business Intelligence: timed mock paper 1 — 180 minutes, 30 objective questions plus written and computational tasks
  • Data Analytics & Business Intelligence: timed mock paper 2 — 180 minutes, 30 objective questions plus written and computational tasks

Lesson pages, assessed tasks and mock papers open the moment you join this programme. Teaching material is studied online; the notes you write are yours to download.

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