Corporate Business Alliance

CBA-DAP · Study material

Contents

The complete contents of the CBA Certified Data Analytics Professional study material: every chapter and lesson, the reading time of each, and where the assessed workbooks fall. One lesson is open to read in full.

Lessons

93

Reading time

5 hours

Workbooks

18

Words

59,809

These figures are counted from the material itself. The reading time assumes a steady pace and no re-reading, and does not include the time spent building the workbooks.

Free, no account

Read a complete lesson

Confidence intervals and margin of error, from Statistical Foundations for Analysts, as a candidate reads it, slides included.

Read the lesson

Contents

7 chapters, 93 lessons. Lessons marked workbook carry a spreadsheet you build and submit, marked against the published tolerance. The award requires 4 of the 18 completed to that tolerance.

Introduction

1 lesson · 2 min

  1. CBA-DAP Study Guide2 min

01Statistical Foundations for Analysts

18 lessons · 64 min

  1. What this chapter covers2 min
  2. The case organisation and the numbers this guide is built from4 min
  3. Populations and samples, and what a sample can support3 min
  4. Levels of measurement, and why they decide the legitimate summary4 min
  5. Centre: the mean, the median, the mode, and the weighted mean7 min
  6. Spread: range, variance, standard deviation and the interquartile range4 min
  7. Distributions, skew, and the bimodal caseworkbook3 min
  8. Outliers: finding them, and the judgement about excluding them4 min
  9. Grain: counting things once3 min
  10. Rates over time, and why a cohort is different from an average4 min
  11. Sampling, and the ways a sample lies3 min
  12. Confidence intervals and margin of errorFreeworkbook4 min
  13. Hypothesis testing, conceptually3 min
  14. Correlation, and the three reasons it is not causation4 min
  15. A/B testing: what makes a test valid, and why peeking breaks itworkbook4 min
  16. Base rates, and reading a model's accuracy honestly2 min
  17. Common pitfalls3 min
  18. Chapter summary3 min

02Preparing and Structuring Data

16 lessons · 51 min

  1. What this chapter covers2 min
  2. Why preparation dominates the work, and why nobody sees it2 min
  3. Data types, and what coercion quietly does4 min
  4. Rows, columns and the grain of a table5 min
  5. Wide and long, and pivoting between them3 min
  6. Keys, cardinality and what joins do to row counts4 min
  7. Fan-out: the duplicate rows a one-to-many join createsworkbook3 min
  8. Deduplication, and what a duplicate actually is3 min
  9. Missing data: absent, zero and unknown are three different things3 min
  10. Profiling an extract before you trust itworkbook5 min
  11. Slowly changing dimensions, validity dates, and the churn queryworkbook5 min
  12. Building a cohort, which is grain and validity at the same time3 min
  13. The label is data too: preparation and the churn model2 min
  14. Reproducibility: the same question, twice3 min
  15. Common pitfalls2 min
  16. Chapter summary2 min

03Analysis with Spreadsheets and SQL Concepts

15 lessons · 54 min

  1. What this chapter covers2 min
  2. Conditional aggregation: SUMIFS, COUNTIFS, and the filter you did not writeworkbook6 min
  3. Lookups: exact match, approximate match, and the missing match you turned into a zero4 min
  4. Pivot tables, and what a pivot is actually doing4 min
  5. When a spreadsheet stops being the right tool2 min
  6. SQL as sets, and the order in which a query is actually evaluated3 min
  7. Grain, aggregation, and the fan-out joinworkbook5 min
  8. NULL: where correct-looking queries go wrong3 min
  9. Subqueries and common table expressions, for readability rather than cleverness2 min
  10. Window functions: keeping every row and answering about the set4 min
  11. Cohort analysis, built step by stepworkbook7 min
  12. Time series: periods, time zones, and comparing like with likeworkbook4 min
  13. Verifying a formula, a query, or a draft written by an assistant4 min
  14. Common pitfalls2 min
  15. Chapter summary2 min

04Visualisation and Dashboards

17 lessons · 48 min

  1. What this chapter covers2 min
  2. Start with the question, not with the chart galleryworkbook2 min
  3. The workhorse forms, and where each one breaks5 min
  4. Axis integrity: baselines, truncation, dual axes and log scalesworkbook4 min
  5. Composition: what stacking can and cannot show4 min
  6. Colour that encodes, and colour that decorates2 min
  7. Designing for colour vision deficiency and the greyscale printout2 min
  8. Labelling, annotation and the title that states the finding2 min
  9. When a table beats a chart9 min
  10. What a dashboard is for2 min
  11. Monitoring and exploratory dashboards are different objects2 min
  12. Choosing the measures, and the layout that puts attention first2 min
  13. Refresh cadence matched to decision cadence2 min
  14. Ashcombe's 34 tiles, triagedworkbook2 min
  15. Accessibility, and the cost of a dashboard nobody opens2 min
  16. Common pitfalls2 min
  17. Chapter summary2 min

05Communicating Insight

11 lessons · 31 min

  1. What this chapter covers2 min
  2. A finding is true; an insight changes something4 min
  3. The ninety-second structureworkbook2 min
  4. Writing a headline that carries the finding2 min
  5. Knowing what your audience can actually change5 min
  6. Quantifying uncertainty without losing the room4 min
  7. Handling a challenge to your numbers2 min
  8. The ethics of presentation3 min
  9. Recommending rather than reportingworkbook3 min
  10. Common pitfalls2 min
  11. Chapter summary2 min

06Introduction to Predictive Methods

15 lessons · 39 min

  1. What this chapter covers2 min
  2. Where prediction belongs, and where a rule or a description is better3 min
  3. Supervised and unsupervised, without the jargon2 min
  4. The unit of prediction: deciding what one row means5 min
  5. Cohorts: the shape the blended rate hides2 min
  6. Regression for prediction, and the emptiness of R squared3 min
  7. Classification, the confusion matrix, and the base rateworkbook3 min
  8. Precision, recall and what each error costsworkbook3 min
  9. Training, validation and test, and what overfitting looks like2 min
  10. Leakage: information that will not exist when you need it2 min
  11. Feature thinking, without writing any feature code2 min
  12. Time series: trend, seasonality and the baseline the model must beatworkbook3 min
  13. Explaining the output, and the limits of the claim3 min
  14. Common pitfalls2 min
  15. Chapter summary2 min

What the material is

The study material is written to the discipline’s domains and learning objectives, chapter by chapter, with worked examples and unscored checks in the lessons and assessed workbooks where the level requires applied work. It does not contain a bank of practice questions matching the examination; the specimen paper shows the style and standard of the examination, with a written rationale for every option.

Back to CBA-DAPCertification scheme