Azure Data Warehouse Quiz

When should you use Azure Synapse Analytics?

• To perform very complex queries and aggregations

• To create dashboards from tabular data

• To enable large number of users to query analytics data

Answer explanation

Azure Synapse Analytics is ideal for performing very complex queries and aggregations due to its powerful analytical capabilities, making it suitable for handling large datasets and intricate data processing tasks.

What is the purpose of data ingestion?

• To perform complex data transformations over data received from external sources

• To capture data flowing into a data warehouse system as quickly as possible

• To visualize the results of data analysis

Answer explanation

The purpose of data ingestion is to capture data flowing into a data warehouse system as quickly as possible, enabling timely access to fresh data for analysis and decision-making.

What is the primary difference between a data lake and a data warehouse?

• A data lake contains structured information, but a data warehouse holds raw business data

• A data lake holds raw data, but a data warehouse holds structured information

• Data stored in a data lake is dynamic, but information stored in a data warehouse is static

Answer explanation

The correct choice is that a data lake holds raw data, while a data warehouse contains structured information. This distinction highlights the different purposes and data organization methods of each system.

Which component of an Azure Data Factory can be triggered to run data ingestion tasks?

• CSV File

• Pipeline

• Linked service

Answer explanation

In Azure Data Factory, a Pipeline is the component that orchestrates and triggers data ingestion tasks. It defines the workflow for data movement and transformation, making it the correct choice.

When might you use PolyBase?

• To query data from external data sources from Azure SQL Database

• To ingest streaming data using Azure Databricks

• To orchestrate activities in Azure Data Factory

Answer explanation

PolyBase is used to query data from external data sources directly within Azure SQL Database, allowing seamless integration and analysis of data stored outside the database.

Which of these services can be used to ingest data into Azure Synapse Analytics?

• Azure Data Factory

• Power BI

• Azure Active Directory

Answer explanation

Azure Data Factory is specifically designed for data integration and can ingest data into Azure Synapse Analytics. Power BI is primarily for data visualization, and Azure Active Directory is for identity management.

You have a large amount of data held in files in Azure Data Lake storage. You want to retrieve the data in these files and use it to populate tables held in Azure Synapse Analytics. Which processing option is most appropriate?

• Use Azure Synapse Link to connect to Azure Data Lake storage and download the data

• Synapse SQL pool

• Synapse Spark pool

Answer explanation

Using Azure Synapse Link allows seamless integration with Azure Data Lake storage, enabling efficient data retrieval and direct loading into Azure Synapse Analytics tables, making it the most appropriate choice.

Which of the components of Azure Synapse Analytics allows you to train AI models using AzureML?

• Synapse Studio

• Synapse Pipelines

• Synapse Spark

Answer explanation

Synapse Studio is the component of Azure Synapse Analytics that integrates with AzureML, allowing users to train AI models directly within its environment, making it the correct choice for this question.

In Azure Databricks how do you change the language a cell uses?

• The first line in the cell is %language. For example, %scala

• Change the notebook language before writing the commands

• Wrap the command in the cell with ##language##

Answer explanation

In Azure Databricks, you can change the language of a cell by adding a magic command at the first line, such as %scala for Scala. This specifies the language for the cell, making it the correct choice.

What is the common flow of activity in Power BI?

• Create a report in Power BI mobile, share it to the Power BI Desktop, view and interact in the Power BI service

• Create a report in the Power BI service, share it to Power BI mobile, interact with it in Power BI Desktop

• Bring data into Power BI Desktop and create a report, share it to the Power BI service, view and interact with reports and dashboards in the service and Power BI mobile

• Bring data into Power BI mobile, create a report, then share it to Power BI Desktop

Answer explanation

The correct flow in Power BI involves bringing data into Power BI Desktop, creating a report, sharing it to the Power BI service, and then viewing and interacting with reports and dashboards in both the service and Power BI mobile.