Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a Fabric tenant that contains a semantic model named Model1.
You discover that the following query performs slowly against Model1.
You need to reduce the execution time of the query.
Solution: You replace line 4 by using the following code:
Does this meet the goal?
You have a Fabric tenant that contains a lakehouse named lakehouse1. Lakehouse1 contains a table named Table1.
You are creating a new data pipeline.
You plan to copy external data to Table1. The schema of the external data changes regularly.
You need the copy operation to meet the following requirements:
* Replace Table1 with the schema of the external data.
* Replace all the data in Table1 with the rows in the external data.
You add a Copy data activity to the pipeline. What should you do for the Copy data activity?
For the Copy data activity, from the Destination tab, setting Table action to Overwrite (B) will ensure that Table1 is replaced with the schema and rows of the external data, meeting the requirements of replacing both the schema and data of the destination table. Reference = Information about Copy data activity and table actions in Azure Data Factory, which can be applied to data pipelines in Fabric, is available in the Azure Data Factory documentation.
You have a Microsoft Power Bl semantic model.
You need to identify any surrogate key columns in the model that have the Summarize By property set to a value other than to None. The solution must minimize effort.
What should you use?
To identify surrogate key columns with the 'Summarize By' property set to a value other than 'None,' the Best Practice Analyzer in Tabular Editor is the most efficient tool. The Best Practice Analyzer can analyze the entire model and provide a report on all columns that do not meet a specified best practice, such as having the 'Summarize By' property set correctly for surrogate key columns. Here's how you would proceed:
Open your Power BI model in Tabular Editor.
Go to the Advanced Scripting window.
Write or use an existing script that checks the 'Summarize By' property of each column.
Execute the script to get a report on the surrogate key columns that do not have their 'Summarize By' property set to 'None'.
You can then review and adjust the properties of the columns directly within the Tabular Editor.
You have a Fabric tenant that contains a warehouse.
You are designing a star schema model that will contain a customer dimension. The customer dimension table will be a Type 2 slowly changing dimension (SCD).
You need to recommend which columns to add to the table. The columns must NOT already exist in the source.
Which three types of columns should you recommend? Each correct answer presents part of the solution.
NOTE: Each correct answer is worth one point.
For a Type 2 slowly changing dimension (SCD), you typically need to add the following types of columns that do not exist in the source system:
An effective start date and time (E): This column records the date and time from which the data in the row is effective.
An effective end date and time (A): This column indicates until when the data in the row was effective. It allows you to keep historical records for changes over time.
A surrogate key (C): A surrogate key is a unique identifier for each row in a table, which is necessary for Type 2 SCDs to differentiate between historical and current records.
You have a Fabric tenant.
You are creating a Fabric Data Factory pipeline.
You have a stored procedure that returns the number of active customers and their average sales for the current month.
You need to add an activity that will execute the stored procedure in a warehouse. The returned values must be available to the downstream activities of the pipeline.
Which type of activity should you add?
In a Fabric Data Factory pipeline, to execute a stored procedure and make the returned values available for downstream activities, the Lookup activity is used. This activity can retrieve a dataset from a data store and pass it on for further processing. Here's how you would use the Lookup activity in this context:
Add a Lookup activity to your pipeline.
Configure the Lookup activity to use the stored procedure by providing the necessary SQL statement or stored procedure name.
In the settings, specify that the activity should use the stored procedure mode.
Once the stored procedure executes, the Lookup activity will capture the results and make them available in the pipeline's memory.
Downstream activities can then reference the output of the Lookup activity.
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