UUY-DTS 2112 units200 LevelFirst Semester

Introduction to Data Analytics

B.Sc. Data Science, University of Uyo

Analytics as a business discipline: the four analytics types (descriptive, diagnostic, predictive, prescriptive), KPI design, dashboarding, and turning an analysis into a decision. Practical and tool-focused.

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Course outline

  1. 01The analytics maturity ladder: descriptive, diagnostic, predictive and prescriptive analytics
  2. 02Defining metrics and KPIs; leading vs lagging indicators
  3. 03Data preparation for analysis: joins, aggregation, pivoting and derived measures
  4. 04Cohort analysis, funnel analysis and time-series trends
  5. 05Spreadsheet analytics: pivot tables, lookup functions and what-if analysis
  6. 06Business intelligence tools: Power BI / Tableau / Looker Studio fundamentals
  7. 07Dashboard design: audience, hierarchy of information, and avoiding chart junk
  8. 08A/B testing basics and the interpretation of experimental results
  9. 09From insight to recommendation: writing the analytics brief

Recommended textbooks

  • Storytelling with Data — Cole Nussbaumer Knaflic

    The best book on communicating an analysis; short and practical

  • Data Science for Business — Foster Provost & Tom Fawcett

    Excellent on why an analysis matters commercially

How to pass UUY-DTS 211

  • Build one real dashboard on a dataset you care about — a portfolio dashboard is worth more at interview than a grade
  • The four analytics types are a guaranteed exam question; be ready with a Nigerian example of each
  • Practise writing a three-sentence "so what" for every chart you make. If you cannot, the chart is not finished
  • Learn pivot tables properly — an enormous amount of professional analytics still happens in a spreadsheet

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