DP-600 Printable PDF - DP-600 Certification Questions
DP-600 Printable PDF - DP-600 Certification Questions
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Microsoft DP-600 Exam Syllabus Topics:
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Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q67-Q72):
NEW QUESTION # 67
You have a Fabric tenant that contains a warehouse.
You use a dataflow to load a new dataset from OneLake to the warehouse.
You need to add a Power Query step to identify the maximum values for the numeric columns.
Which function should you include in the step?
- A. Table.Profile
- B. Table. MaxN
- C. Table.Max
- D. Table.Range
Answer: C
Explanation:
The Table.Max function should be used in a Power Query step to identify the maximum values for the numeric columns. This function is designed to calculate the maximum value across each column in a table, which suits the requirement of finding maximum values for numeric columns. Reference = For detailed information on Power Query functions, including Table.Max, please refer to Power Query M function reference.
NEW QUESTION # 68
You have a Fabric tenant that contains a data warehouse named DW1. DW1 contains a table named DimCustomer. DimCustomer contains the fields shown in the following table.
You need to identify duplicate email addresses in DimCustomer. The solution must return a maximum of 1,000 records.
Which four T-SQL statements should you run in sequence? To answer, move the appropriate statements from the list of statements to the answer area and arrange them in the correct order.
Answer:
Explanation:
NEW QUESTION # 69
You are analyzing customer purchases in a Fabric notebook by using PySpanc You have the following DataFrames:
You need to join the DataFrames on the customer_id column. The solution must minimize data shuffling. You write the following code.
Which code should you run to populate the results DataFrame?
- A.
- B.
- C.
- D.
Answer: D
Explanation:
The correct code to populate the results DataFrame with minimal data shuffling is Option A. Using the broadcast function in PySpark is a way to minimize data movement by broadcasting the smaller DataFrame (customers) to each node in the cluster. This is ideal when one DataFrame is much smaller than the other, as in this case with customers. Reference = You can refer to the official Apache Spark documentation for more details on joins and the broadcast hint.
NEW QUESTION # 70
You have a Fabric tenant that contains a workspace named Workspace