DP-600 Exam Dumps - Implementing Analytics Solutions Using Microsoft Fabric

Before specifying the partition column in the Destination settings of the Copy activity, you should set Mode to Append (A). This will allow the Copy activity to add data to the table while taking the partition column into account. References = The configuration options for Copy activities and partitioning in Azure Data Factory, which are applicable to Fabric dataflows, are outlined in the official Azure Data Factory documentation.

The correct DMV to identify what is preventing the report query from completing is sys.dm_pdw_exec_requests (D). This DMV is specific to Microsoft Analytics Platform System (previously known as SQL Data Warehouse), which is the environment assumed to be used here. It provides information about all queries and load commands currently running or that have recently run. References = You can find more about DMVs in the Microsoft documentation for Analytics Platform System.

The correct order for the DAX expression would be:

DEFINE VAR _SalesSince = DATE ( 2023, 12, 01 )

EVALUATE

FILTER (

SUMMARIZE ( Store, Store[Name], Store[OpenDate] ),

Store[OpenDate] >= _SalesSince )

In this DAX query, you're defining a variable _SalesSince to hold the date from which you want to filter the stores. EVALUATE starts the definition of the query. The FILTER function is used to return a table that filters another table or expression. SUMMARIZE creates a summary table for the stores, including the Store[Name] and Store[OpenDate] columns, and the filter expression Store[OpenDate] >= _SalesSince ensures only stores opened on or after December 1, 2023, are included in the results.

References =

DAX FILTER Function

DAX SUMMARIZE Function

The Table.Profile function in Power Query is used to generate column statistics such as count, average, null count, distinct count, and standard deviation. You can use this function as follows:

Invoke the Power Query Editor.

Apply the Table.Profile function to your table.

The result will be a table where each row represents a column from the original table, and each column in the result represents a different statistic such as those listed in the requirement.

A lakehouse (A) is the type of data store you should use. It supports dataflows to load and append data and ensures that Delta tables are Z-Order optimized and compacted automatically. References = The capabilities of a lakehouse and its support for Delta tables are described in the lakehouse and Delta table documentation.

When creating a shortcut to an Azure Data Lake Storage Gen2 account in a lakehouse, you should use the abfss (Azure Blob File System Secure) connection string and the dfs (Data Lake File System) endpoint. The abfss is used for secure access to Azure Data Lake Storage, and the dfs endpoint indicates that the Data Lake Storage Gen2 capabilities are to be used.

Comprehensive Detailed Explanation

When assigning permissions to roles in a Fabric workspace for analytics workloads, you must align permissions with the responsibilities and tools typically used by each persona:

1. Data Engineers

Their primary tasks include building and transforming data pipelines, as well as making datasets usable by others.

The appropriate permission is Build Reports on the default dataset, because this allows them to create and manage reports using the curated semantic model while preparing data for analysts and scientists.

2. Data Analysts

Analysts work heavily with Apache Spark for exploratory analysis, cleansing, and shaping data.

The correct permission is Read All Apache Spark, as this grants them the ability to query and analyze Spark-based data directly without elevated permissions that are unnecessary for their role.

3. Data Scientists

Data scientists often use SQL analytics endpoints to run queries, train models, and integrate data into machine learning workflows.

The correct permission is Read All SQL analytics endpoint data, since it enables direct programmatic access to the SQL endpoint, which is needed for advanced modeling and experimentation.

Summary of Selections:

DataEngineers → Build Reports on the default dataset

DataAnalysts → Read All Apache Spark

DataScientists → Read All SQL analytics endpoint data

References (Microsoft Fabric – DP-600 exam scope):

Workspace roles and permissions in Microsoft Fabric

SQL analytics endpoint in Fabric

Apache Spark in Microsoft Fabric

The measure should use the AVERAGE function to calculate the average value.

It should reference the Response Value column from the 'Survey' table.

The 'Number of months' should be used to define the period for the average calculation.

To calculate the average overall satisfaction score using DAX, you would need to use the AVERAGE function on the response values related to satisfaction questions. The DATESINPERIOD function will help in calculating the rolling average over the last 12 months.