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  1. Home
  2. CompTIA Certification
  3. DA0-001 Exam
  4. CompTIA.DA0-001.v2022-08-24.q50 Dumps
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Question 21

What is NOT a characteristic of a good data steward?

Correct Answer: A
Provide the technical expertise around source systems, extract, transform, and load (ETL) processes, data stores, data warehouses, and Business intelligence tools.
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Question 22

Which dimension of data quality ensures that data stored in multiple locations is the same?

Correct Answer: D
Data consistency means that each user sees a consistent view of the data, including visible changes made by the user's own transactions and transactions of other users.
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Question 23

The ACME Corporation hired an analyst to detect data quality issues in their excel documents. Which of the following are the most common issues? (Select TWO)

Correct Answer: D,E
1. Duplicates
2. Misspellings
The most common data quality issues are difficult to resolve in Excel because of their rigidity. It forces analysts to do a ton of manual work, which results in a high probability of an error being introduced to the data set. Those common issues include:
- Blanks
- Nulls
- Outliers
- Duplicates
- Extra spaces
- Misspellings
- Abbreviations and domain-specific variations
- Formula error codes
When introduced, these errors can skew or even invalidate the resulting analysis. A smart tool would minimize the possibility of error by automating the manual work. In Excel, you might look for data quality issues in one of two ways. First, you might use auto filters on specific columns to scan for anomalies and blanks or you might use a pivot table to find gaps and discrepancies.
In either case, you're scanning for the anomalies yourself. Suffice it to say that's not a very efficient process. It also means accuracy is only as good as the analyst's eye, so the probability of error varies throughout the day.
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Question 24

What type of access permission system is most appropriate for a dashboard?

Correct Answer: B
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Question 25

A data analyst wants to create "Income Categories" that would be calculated based on the existing variable "Income". The "Income Categories" would be as follows:
Income category 1: less than $1.
Income category 2: more than $1 and less than $20,000.
Income category 3: more than $20,001 and less than $40,000.
Income category 4: more than $40,001.
Which of the following data manipulation techniques should the data analyst use to create "Income Categories"?

Correct Answer: B
The correct answer is B: Derived variables Derived variables are variables that you create by calculating or categorizing variables that already exist in your data set.
Data merge is incorrect. Data merging is the process of combining two or more data sets into a single data set. Data blending is incorrect.
Data blending involves pulling data from different sources and creating a single, unique, dataset for visualization and analysis.
Data append is incorrect. A data append is a process that involves adding new data elements to an existing database.
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