IV.4 Manage data transformation to conduct data preparation

Enablers (verbatim, ECO)

PMI, ECO p. 5: enablers are "illustrative examples of the work associated with the task" and "not meant to be an exhaustive list but rather offer a few examples to help demonstrate what the task encompasses."

Ours: PMI's stems paraphrase one of these as a symptom; the right option is that enabler in PMI's words; the distractors are its siblings or a neighbouring task's enablers.

1. Oversee data cleaning and preprocessing workflows
2. Coordinate feature engineering and selection activities
3. Manage data normalization and standardization processes
4. Supervise data augmentation and synthetic data generation
5. Ensure data transformation reproducibility and documentation

Study Hall misses on this task (3)

• Full-length Q108 · confidence High · 22s
  Scenario: Cleaning and preprocessing complete; NEXT (Phase III sequence)
  Decided by: Feature engineering and selection
  Chose: Going back to exploratory analysis
• Full-length Q7 · confidence Medium · 71s
  Scenario: Stem asks directly about overseeing data transformation; options were the four Domain IV tasks
  Decided by: Answer with IV.4's own enabler (oversee cleaning, manage standardisation)
  Chose: The IV.5 gate option
• Full-length Q81 · confidence High · 14s
  Scenario: Hundreds of irrelevant columns; which technique (Module 03 vocabulary)
  Decided by: Attribute pruning
  Chose: Normalisation

Nothing logged yet.

What to read

• Workbook p. 62-68 — Select Data; Clean Data; Enhance and Augment Data; Label Data
• Module 03 Lessons 19-21: Data Cleansing and Enhancement; Lessons 26-29: Transformation and Augmentation; Lessons 31-32: Data Labeling
• Leading and Managing AI Projects p. 23-24 — Understanding Data Transformation Requirements; Key Activities and Deliverables in Phase III
• Study guide Lesson 1: ECO Task IV.4 — Manage Data Transformation to Conduct Data Preparation