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Databricks Certified Data Analyst Associate Exam Sample Questions (Q54-Q59):
NEW QUESTION # 54
Which statement describes descriptive statistics?
- A. A branch of statistics that uses a variety of data analysis techniques to infer properties of an underlying distribution of probability.
- B. A branch of statistics that uses summary statistics to categorically describe and summarize data.
- C. A branch of statistics that uses summary statistics to quantitatively describe and summarize data.
- D. A branch of statistics that uses quantitative variables that must take on a finite or countably infinite set of values.
Answer: C
NEW QUESTION # 55
The stakeholders.customers table has 15 columns and 3,000 rows of dat
a. The following command is run:
After running SELECT * FROM stakeholders.eur_customers, 15 rows are returned. After the command executes completely, the user logs out of Databricks.
After logging back in two days later, what is the status of the stakeholders.eur_customers view?
- A. The view remains available but attempting to SELECT from it results in an empty result set because data in views are automatically deleted after logging out.
- B. The view remains available and SELECT * FROM stakeholders.eur_customers will execute correctly.
- C. The view has been dropped.
- D. The view has been converted into a table.
- E. The view is not available in the metastore, but the underlying data can be accessed with SELECT * FROM delta. `stakeholders.eur_customers`.
Answer: B
Explanation:
In Databricks, a view is a saved SQL query definition that references existing tables or other views. Once created, a view remains persisted in the metastore (such as Unity Catalog or Hive Metastore) until it is explicitly dropped.
Key points:
Views do not store data themselves but reference data from underlying tables.
Logging out or being inactive does not delete or alter views.
Unless a user or admin explicitly drops the view or the underlying data/table is deleted, the view continues to function as expected.
Therefore, after logging back in-even days later-a user can still run SELECT * FROM stakeholders.eur_customers, and it will return the same data (provided the underlying table hasn't changed).
NEW QUESTION # 56
In which circumstance will there be a substantial difference between the variable's mean and median values?
- A. When the variable contains a lot of extreme outliers
- B. When the variable is of the boolean type
- C. When the variable contains no outliers
- D. When the variable is of the categorical type
Answer: A
Explanation:
The mean is sensitive to extreme values, often called outliers, which can significantly skew the average away from the true center of the data. The median, however, is a measure of central tendency that is resistant to such outliers because it only considers the middle value(s) when the data is ordered. Therefore, when a variable contains many extreme outliers, there will be a substantial difference between the mean and the median. According to Databricks data analysis materials, this is a fundamental concept when choosing summary statistics for reporting.
NEW QUESTION # 57
In which of the following situations will the mean value and median value of variable be meaningfully different?
- A. When the variable contains no missing values
- B. When the variable contains a lot of extreme outliers
- C. When the variable is of the boolean type
- D. When the variable contains no outliers
- E. When the variable is of the categorical type
Answer: B
Explanation:
The mean value of a variable is the average of all the values in a data set, calculated by dividing the sum of the values by the number of values. The median value of a variable is the middle value of the ordered data set, or the average of the middle two values if the data set has an even number of values. The mean value is sensitive to outliers, which are values that are very different from the rest of the data. Outliers can skew the mean value and make it less representative of the central tendency of the data. The median value is more robust to outliers, as it only depends on the middle values of the data. Therefore, when the variable contains a lot of extreme outliers, the mean value and the median value will be meaningfully different, as the mean value will be pulled towards the outliers, while the median value will remain close to the majority of the data1. Reference: Difference Between Mean and Median in Statistics (With Example) - BYJU'S
NEW QUESTION # 58
Which of the following statements about a refresh schedule is incorrect?
- A. A query can be refreshed anywhere from 1 minute lo 2 weeks
- B. A query being refreshed on a schedule does not use a SQL Warehouse (formerly known as SQL Endpoint).
- C. A refresh schedule is not the same as an alert.
- D. Refresh schedules can be configured in the Query Editor.
- E. You must have workspace administrator privileges to configure a refresh schedule
Answer: B
Explanation:
Refresh schedules are used to rerun queries at specified intervals, and these queries typically require computational resources to execute. In the context of a cloud data service like Databricks, this would typically involve the use of a SQL Warehouse (or a SQL Endpoint, as they were formerly known) to provide the necessary computational resources. Therefore, the statement is incorrect because scheduled query refreshes would indeed use a SQL Warehouse/Endpoint to execute the query.
NEW QUESTION # 59
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