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Salesforce Exam Salesforce AI Associate Topic 1 Question 40 Discussion

Actual exam question for Salesforce's Salesforce AI Associate exam
Question #: 40
Topic #: 1
[All Salesforce AI Associate Questions]

What are the key components of the data quality standard?

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Suggested Answer: B

''Accuracy, Completeness, Consistency are the key components of the data quality standard. Data quality standard is a set of criteria or measures that define and evaluate the quality of data for a specific purpose or task. Data quality standard can vary by industry, domain, or application, but some common components are accuracy, completeness, and consistency. Accuracy means that the data values are correct and valid for the data attribute. Completeness means that the data values are not missing any relevant information for the data attribute. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources.''


by Irene at Mar 22, 2025, 04:20 AM

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Lynelle
9 days ago
B) Accuracy, Completeness, Consistency - the data quality triple threat, baby! *flexes data muscles*
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Margurite
12 days ago
C) Reviewing, Updating, Archiving - gotta keep that data squeaky clean, am I right?
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Wynell
15 days ago
I think it's a combination of both sets of components, they all play a role in ensuring data quality.
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Sommer
16 days ago
I believe Naming, Formatting, Monitoring are also crucial for data quality.
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Cammy
19 days ago
B) Accuracy, Completeness, Consistency - the trifecta of data quality nirvana! *mic drop*
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Terrilyn
2 days ago
A) Naming, formatting, Monitoring - those are important too!
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Gearldine
22 days ago
I agree with Quiana, those are important for data quality.
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Milly
24 days ago
Wait, is there an option for 'All of the above'? Seems like they're all pretty important to me.
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Cecily
25 days ago
B) Accuracy, Completeness, Consistency - easy peasy, that's the data quality holy trinity!
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Quiana
26 days ago
I think the key components are Accuracy, Completeness, Consistency.
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France
28 days ago
A) Naming, formatting, Monitoring - those are the essential building blocks for data quality, no doubt about it.
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Edison
5 days ago
B) Accuracy, Completeness, Consistency - those are also crucial components to ensure high data quality.
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Gladys
16 days ago
A) Naming, formatting, Monitoring - those are the essential building blocks for data quality, no doubt about it.
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Rikki
1 months ago
Hmm, I'd go with C) Reviewing, Updating, Archiving. Gotta make sure your data stays fresh, you know?
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Maryann
1 months ago
B) Accuracy, Completeness, Consistency - that's the classic data quality framework right there!
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