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Dama CDMP-RMD Exam - Topic 1 Question 21 Discussion

Actual exam question for Dama's CDMP-RMD exam

Question #: 21
Topic #: 1

[All CDMP-RMD Questions]

MDM matching algorithms benefit from all of the following data characteristics except for which of the following?

ADistinctiveness across the population of data

BLow number of common data points

CHigh level of comparability of the data elements

DStructural heterogeneity of data elements

EHigh validity of the data

Show Suggested Answer

Suggested Answer: D

Every process within an MDM framework includes a degree of governance. Here's why:

Governance Definition:

Policies and Standards: Governance involves the establishment of policies, standards, and procedures to ensure data quality, consistency, and compliance.

Oversight: Provides oversight and accountability for data management practices.

MDM Processes:

Inherent Governance: All MDM processes, from data integration to data quality management, incorporate governance to ensure the integrity and reliability of master data.

Data Stewardship: Involves data stewards who oversee data governance activities, ensuring adherence to established standards and policies.

Data Management Body of Knowledge (DMBOK), Chapter 7: Master Data Management

DAMA International, 'The DAMA Guide to the Data Management Body of Knowledge (DMBOK)'

by Alba at Jan 13, 2025, 01:12 AM

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Sabra

6 months ago

A is crucial, distinctiveness is key for accurate matching!

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Amie

6 months ago

I agree with techSavvy, D seems off for MDM matching.

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Joni

7 months ago

Wait, are we sure about E? High validity should help, right?

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Frederica

7 months ago

I think D is the answer, structural heterogeneity can confuse algorithms.

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Rosalyn

7 months ago

Definitely not B, low common data points are a problem!

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Yesenia

7 months ago

High validity of data seems crucial for accuracy, so I would lean towards option B as the exception.

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Marnie

8 months ago

I practiced a similar question where structural heterogeneity was a factor, but I can't recall if it's beneficial or not here.

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Bronwyn

8 months ago

I think low common data points might actually hinder the matching process, but I need to double-check that.

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Raul

8 months ago

I remember that distinctiveness is important for MDM algorithms, but I'm not sure about the role of common data points.

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Precious

8 months ago

This question seems straightforward. I'll eliminate the options that do benefit MDM matching and select the one that doesn't.

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Clement

8 months ago

I'm confident I can solve this. The answer is structural heterogeneity of data elements, as that would make it harder for the algorithms to match the data.

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Makeda

8 months ago

Okay, I've got this. The key is to identify the data characteristic that does NOT benefit MDM matching algorithms.

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Leonard

8 months ago

Hmm, I'm a bit unsure about this one. I'll need to review my notes on MDM matching algorithms and data characteristics.

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Noah

8 months ago

This looks like a tricky question. I'll need to think carefully about the data characteristics that benefit MDM matching algorithms.

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Omer

1 year ago

Oh man, this is like a game of data matching tetris! I'm gonna go with D, just to keep things interesting.

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Miesha

1 year ago

Hold up, is that a trick question? I bet the answer is C, high level of comparability of the data elements. Gotta keep those data points in line, am I right or am I right?

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Samira

1 year ago

I'm not so sure about that, I think the correct answer is A, distinctiveness across the population of data.

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Elenora

1 year ago

I see where you're coming from, but I believe the answer is E, high validity of the data.

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Ma

1 year ago

I think you might be onto something, but I'm leaning towards D, structural heterogeneity of data elements.

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Andra

1 year ago

Okay, let's think this through. I'm gonna go with E, high validity of the data. Can't have those algorithms matching up junk data, you know?

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Avery

12 months ago

I see your point, but I still think E is the most important factor for accurate matching.

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Patrick

1 year ago

I think it's actually D, structural heterogeneity of data elements that is not beneficial for MDM matching algorithms.

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Deja

1 year ago

I agree, high validity of the data is crucial for accurate matching.

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Mauricio

1 year ago

Woah, this question is tricky! I'm leaning towards B, low number of common data points. Gotta love those unique data sets, am I right?

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Dortha

1 year ago

Hmm, I think the correct answer is D. Structural heterogeneity of data elements. That's the only one that doesn't seem to benefit the matching algorithms, right?

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Jacqueline

1 year ago

No, I think E would actually benefit the matching algorithms. It's probably D.

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Lindsey

1 year ago

Yeah, D doesn't really help with matching algorithms like the other options do.

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Hermila

1 year ago

I agree, D does seem like the odd one out.

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Lindsey

1 year ago

I'm not so sure, I think it might be E. High validity of the data.

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Alonzo

1 year ago

Yeah, I think so too. The other options all sound like they would help with matching.

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Esteban

1 year ago

I agree, D seems like the odd one out.

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Florinda

1 year ago

I'm not sure, but I think E) High validity of the data could also be a correct answer, as accurate and reliable data is crucial for matching algorithms.

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Tamesha

1 year ago

I agree with Laurel, because MDM matching algorithms need data elements to be structurally similar for accurate matching.

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Laurel

1 year ago

I think the answer is D) Structural heterogeneity of data.

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