Domain III: Identify Data Needs — Study Game

How to Play

Pick a game mode and test yourself. Cover the answers and try to recall before peeking.

Defining Required Data (III.1)

Card 1 — Front: What's the output of ECO Task III.1?

Answer: A documented data requirements specification (not a dataset).

Answer: Determine pattern, Required attributes, Identify sources, Plan aggregation.

Card 2 — Front: Required data is defined ____ collection, not during it.

Answer: before.

Card 3 — Front: What drives the data type required?

Answer: The AI pattern from Phase I (Recognition→images, Predictive→structured, Conversational→text).

Sources, SMEs, Infrastructure (III.2-III.5)

Answer: Source type, Cost & access, Accuracy & cadence, Legal/license, Endpoint.

Card 4 — Front: Distinguish data steward from data custodian.

Answer: Steward = strategic, policy-enforcing, cross-functional. Custodian = operational, NOT the data owner.

Card 5 — Front: What does ECO III.4 cover?

Answer: Coordinate AI workspace and infrastructure (compute, storage, pipelines, environments, security, access).

Card 6 — Front: Who executes data gathering in III.5?

Answer: Data engineering team. PM coordinates and tracks.

Privacy, Compliance, Bias (III.6 + cross-pulls)

Card 7 — Front: Privacy/compliance checks belong in which phase?

Answer: Phase II (Data Understanding) per ECO III.6 — NOT Phase III.

Card 8 — Front: Difference between anonymization and pseudonymization?

Answer: Anonymization is irreversible (no longer PII). Pseudonymization is reversible (still PII under GDPR).

Card 9 — Front: Three types of bias in AI?

Answer: Neural-network (math), Variance (fitting), Informational (fairness — exam one)..

Card 10 — Front: Three types of informational bias?

Answer: Reporting (some aspects recorded), Recall (recent vs old data weighted), Classification (data categorized to misrepresent groups).

The 4 Vs of Big Data

Card 11 — Front: What are the 4 Vs?

Answer: Volume, Velocity, Variety, Veracity..

Card 12 — Front: Volume challenge in big data?

Answer: Massive amounts spread across locations (we're in zettabyte era).

Card 13 — Front: Velocity challenge?

Answer: Rapidly changing data OR moving data quickly between locations.

Card 14 — Front: Variety challenge?

Answer: Different formats — structured, unstructured, semistructured. One system can't handle all three.

Card 15 — Front: Veracity challenge?

Answer: Different levels of quality, accuracy, trustworthiness. Hard to assess at scale.

Data Quality Dimensions

Answer: Accuracy, Completeness, Consistency, Timeliness, Uniqueness, Validity, Integrity. "A Cat Caught Two Unwary Voles Inside."

Data Types

Card 16 — Front: What % of organizational data is unstructured?

Answer: ~80%.

Card 17 — Front: Three data type categories?

Answer: Structured (defined schema), Unstructured (no schema), Semi-structured (partial schema).

Card 18 — Front: What's training data?

Answer: Prepared, cleaned, labeled data used to train an ML model.

Card 19 — Front: What's ground truth data?

Answer: Definitive reference data the model is measured against.

The Gate (III.8)

Card 20 — Front: Three areas evaluated at III.8 gate?

Answer: Sources, Description, Quality..

Card 21 — Front: Three outcomes at III.8?

Answer: GO (proceed to Phase III) / ITERATE (loop back) / DESCOPE (reduce scope).

Card 22 — Front: PMI's key gate concept?

Answer: "If you can confidently say 'We have the data and know the problem,' move to Phase III. If not, pause."

Iteration Triggers

Card 23 — Front: How many iteration triggers does PMI document for Phase II → Phase I loops?

Answer: 12 distinct scenarios (business shift, infeasible data, wrong type, etc.).

Card 24 — Front: Is iterating back to a prior phase a project failure?

Answer: No — it's methodology-correct. CPMAI's iterative design specifically allows backing up "without penalty."

Conveying to Leadership (III.9)

Card 25 — Front: What's the III.9 deliverable?

Answer: Leadership briefing covering data state, gate decision, key risks, recommendations, scope/schedule impacts.

Card 26 — Front: Is III.9 optional?

Answer: No — mandatory leadership communication before Phase III work begins.

Card 27 — Front: What's the cross-pull from III.9 → V.5?

Answer: III.9 conveyance feeds Domain V's final report; gate decisions become lessons-learned content.

GAME MODE 2: Scenario Showdown — What Should the PM Do?

Scenario 1: The Pattern Mismatch

Team is defining required data for a project where Phase I selected the Recognition AI pattern
Available data is structured tabular, not labeled images
Data scientist suggests changing the pattern to Predictive Analytics
Team is in Phase II

Reveal

Loop back to Phase I (II.7) to revisit the AI pattern selection with stakeholders. Pattern is a Phase I deliverable; changing it inside Domain III bypasses governance. Engage stakeholders, document the revision, assess scope impact (II.4).

Scenario 2: The Compliance Surprise

BAA required under HIPAA before partner data sharing
Legal estimates 6 weeks for execution
Project schedule wants to start data gathering immediately
Stakeholders not yet engaged

Reveal

Document the delay as a risk, escalate to leadership with options, engage stakeholders. Cross-pull III.6 + III.8 + I.4. Options: proceed-and-wait, iterate to alternative sources, descope. Don't proceed unilaterally.

Scenario 3: The Volume Shortfall

Required volume is 1M records; team gathered 200K
Data scientist suggests synthetic data augmentation
Mid-Phase II
The original technique requires high data volume

Reveal

Pause and engage stakeholders. PMI iteration trigger #4/5. Options: synthetic data (with QA + governance), additional sourcing, technique change, descope. Document decision before proceeding.

Scenario 4: The Quality Gate

All 7 dimensions met
Privacy plan not signed off by legal
Team wants GO at III.8
Stakeholder pressure to keep schedule

Reveal

ITERATE — III.8 includes trustworthy-AI alignment. Privacy plan sign-off is governance gap (I.1 cross-pull). Don't GO with conditional sign-offs that defer governance.

Scenario 5: The Source Disappears

Mid-gathering, an internal source is decommissioned
Data scientist suggests workaround
25% of required data was on this source

Reveal

Loop back to III.3 to identify alternative sources. Iteration trigger. Document inventory revision and assess III.8 gate impact.

Scenario 6: The Bias Discovery

Required dataset shows demographic skew during evaluation
Success criteria from II.8 require fairness across user segments
Data scientist suggests proceeding and adjusting at training time

Reveal

Cross-domain issue: III.7 + I.3 + II.8. Document, engage stakeholders for mitigation options (re-source, rebalance training data, in-processing fairness, post-processing calibration). Don't approve "fix at training time" without governance.

Scenario 7: The PoC Confusion

Mid-Phase II, the team realizes they're doing a Proof-of-Concept (PoC), not a Pilot
Data is sufficient for technical demonstration but not production value proof
Data scientist proposes proceeding as if it's a pilot

Reveal

PMI iteration trigger #12 (PoC vs Pilot misalignment). Loop back to Phase I to redefine project scope as PoC with explicit follow-up plan, OR descope to confirm pilot data requirements.

Scenario 8: The Consent Gap

During privacy check, team discovers training data was collected without consent for AI/ML use
Data scientist suggests anonymizing and proceeding

Reveal

Treat as serious compliance and accountability incident. Escalate to legal/compliance/leadership. Anonymization may not cure consent defects. Cross-pull I.1 + I.4 + I.5.

GAME MODE 3: Pattern Match Challenge

Match each scenario to the right ECO Domain III task:

#	Scenario	Your Answer	Correct ECO Task
1	Defining required data attributes	_____	III.1
2	Identifying data SMEs	_____	III.2
3	Identifying data sources	_____	III.3
4	Coordinating AI workspace	_____	III.4
5	Gathering required data	_____	III.5
6	Privacy/compliance/access check	_____	III.6
7	Overseeing data evaluation	_____	III.7
8	Determining if data meets needs (THE GATE)	_____	III.8
9	Conveying findings to leadership	_____	III.9
10	Defining what 7 quality dimensions mean	_____	(III.7)
11	Documenting source inventory	_____	III.3
12	Engaging data steward	_____	III.2

Scoring: 11-12 correct = Expert | 8-10 = Solid | 5-7 = Review needed | Below 5 = Re-study Module 1

GAME MODE 4: Fill-in-the-Blank Speed Round

The 4 Vs of Big Data are ________, Velocity, Variety, ________.
The III.8 gate has three outcomes: ________, ITERATE, ________.
A data ________ enforces policy; a data ________ ensures safe storage and is NOT the data owner.
The AI pattern from Phase I drives the ________ in Phase II.
ECO III.6 (privacy/compliance/access) cross-pulls primarily to Domain I.1 and Domain ________.
Anonymization is irreversible; ________ is reversible (still PII under GDPR).
PMI lists ________ iteration triggers from Phase II back to Phase I.
Three types of informational bias: ________, recall bias, classification bias.
The III.8 gate evaluates Sources, ________, Quality.
ECO III.5 produces an updated Data Source Inventory + ________ dataset.
Domain III's PM Oversight Angle includes: PM owns / Deliverable / Iteration trigger / Escalation trigger / Wrong-answer trap / Question pattern signal / ________.
Required data spans training, validation, test, and ________ data.
~80% of organizational data is ________.
Ground truth data is the definitive ________ data.
The PM's job in III.7 is to ________ the evaluation, not perform it.

Reveal answers

Volume / Veracity
GO / DESCOPE
steward / custodian
data type
I.4
pseudonymization
12
Reporting bias
Description
staged
ECO task tag
production-inference
unstructured
reference
oversee

GAME MODE 5: True or False Lightning Round

#	Statement	Correct
1	III.1 is complete when the data scientist has a list of required fields	FALSE — needs documented spec with multi-stakeholder sign-off
2	The III.8 gate has three outcomes (GO/ITERATE/DESCOPE)	TRUE
3	Privacy checks belong in Phase III	FALSE — Phase II per III.6
4	Stewards and custodians are the same role	FALSE — strategic vs operational; custodian is NOT the data owner
5	PMI documents 8 iteration triggers from Phase II to Phase I	FALSE — 12 triggers
6	The 4 Vs are Volume, Velocity, Variety, Validity	FALSE — Veracity, not Validity
7	Anonymization is reversible; pseudonymization is irreversible	FALSE — reverse is true
8	The PM coordinates infrastructure but doesn't build it	TRUE
9	Iterating back to Phase I is project failure	FALSE — methodology-correct
10	Required data is defined before collection, not during	TRUE
11	III.9 is an optional formality	FALSE — mandatory leadership communication
12	The data scientist owns the III.7 evaluation	FALSE — team executes; PM oversees
13	Ground truth data is needed for objective evaluation	TRUE
14	Synthetic data substitution requires governance review	TRUE
15	The III.8 gate is point-in-time and irreversible	FALSE — CPMAI is iterative; new info can warrant revisit

Scoring: 14-15 = Exam ready | 11-13 = Almost there | Below 11 = Review the guide

Scoring Summary

Game Mode	Your Score	Max
Flashcards	___/30	30
Scenario Showdown	___/8	8
Pattern Match	___/12	12
Fill-in-the-Blank	___/15	15
True/False	___/15	15
Mnemonic Speed Recall	___/9	9
TOTAL	___/89	89

Rating:

80-89: Domain III mastered — move to next domain
65-79: Strong foundation. Review weak modes once more.
50-64: Re-read the study guide, then try again.
Below 50: Revisit Module 02 source PDF.