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OMBA 102 · Unit 1 of 7

Data Foundations

Data, Statistics and Managerial Decisions

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Learning objectives

After completing this unit, you will be able to:

  • Translate business questions into testable data questions
  • Classify data types and choose appropriate measurement scales
  • Diagnose data quality, missingness, and bias before analysis
  • Structure datasets for reliable analysis in spreadsheets or SQL
  • Apply ethics and governance standards to business data work

Why this matters

Bad conclusions usually start with bad questions and dirty data, not wrong formulas. Unit 1 is the guardrail for everything in OMBA 102: if you skip it, you will run impressive analyses that answer the wrong problem or discriminate by accident.

Unit overview

Work through the five lessons below in order. Bring a dataset or table from work if you have one.

#LessonCore idea
1From Business Questions to Data QuestionsTranslation ladder and SMART tests
2Types of Data and Measurement ScalesNominal, ordinal, interval, ratio
3Data Quality, Missingness, and BiasGarbage in, governance out
4Structuring Data for AnalysisTidy data and schema discipline
5Ethics and Governance in Business DataPrivacy, fairness, and consent

Connection to applied work

Start a data dictionary for your OMBA 102 project dataset: variables, types, sources, known biases, and ethical constraints. Update it after each lesson.

Practice

  1. Rewrite a live business question as three progressively sharper data questions.
  2. Classify ten variables in a sample dataset by type and appropriate summary statistic.
  3. Document missing data patterns and one bias risk in a real or sample table.
  4. Reshape one wide table to tidy long format (even on paper).

Knowledge check

  1. What makes a data question testable?
  2. Why does measurement scale matter for charts and averages?
  3. What is selection bias?
  4. What is tidy data?
  5. When must managers slow down for ethics review?

Key takeaways

  • Data work starts with questions and schema, not software.
  • Measurement and quality choices constrain every later method.
  • Ethics is a design constraint, not a compliance footnote.
  • Complete all lessons before unit assessments.

Unit assessment

Complete each section below. Score 80%+ on the quiz to finish this unit's assessment.

40% applied project35% knowledge checks25% reflections

Exercises

Apply what you learned in this unit with structured practice.

ExerciseApplied practice: Data Foundations45 min
Complete a focused practice exercise on **Data Foundations**. 1. Choose a real company, product, or situation you know. 2. Apply one core framework from this unit to analyze it. 3. Write your analysis in 300–500 words with a clear recommendation. 4. Cite at least one credible source.

Deliverable

300–500 word analysis document saved to your portfolio under OMBA 102.

Rubric

  • • Framework applied correctly (not just named)
  • • Specific evidence from a real example
  • • Clear recommendation with tradeoffs acknowledged
  • • Professional writing with source citation
ExerciseDrill: Data Foundations30 min
Work through the practice problems in the unit lesson without looking at notes. Then check your work against the lesson and write a short reflection: - What you got right - One mistake you caught - One concept to review before the next unit

Deliverable

Problem solutions + 150-word reflection in your OMBA 102 workbook.

Rubric

  • • Attempted all practice items before checking answers
  • • Honest reflection on errors
  • • Identifies a specific review action

Model / spreadsheet

Build or extend a spreadsheet model tied to this unit.

ModelStructured model: Data Foundations60 min
Create a structured analytical model for **Data Foundations**. Document your assumptions, calculations, and conclusions in a format appropriate to OMBA 102 (diagram, table, or written model). Connect outputs to a decision a manager would make.

Deliverable

Structured model document (2+ pages) · One-paragraph summary of key insight from the model · Screenshot or export saved to portfolio

Rubric

  • • Assumptions stated explicitly
  • • Logic is auditable (formulas or steps visible)
  • • Output answers a specific business question
  • • Sensitivity or scenario considered

Knowledge quiz

Check your understanding before marking the unit complete.

1. A CMO asks, 'Did our spring campaign work?' Which is the strongest data question translation?

2. Five-star product ratings are best classified as which measurement scale?

3. Revenue in dollars and units sold are examples of which scale?

4. A survey response is missing only because the respondent skipped an optional question, unrelated to their satisfaction level. This pattern is closest to:

5. For regression and pivot analysis, customer-month metrics are usually stored in which structure?

6. A churn model trained only on customers who completed onboarding ignores those who left during onboarding. The primary risk is:

7. Before sharing employee survey results with managers, which ethics practice is most appropriate?

8. Which element is still missing from: 'What is churn among Pro plan customers in Q1 2026?'

Next unit: Describing Business Performance →