Microsoft Azure Data Fundamentals: Explore data analytics in Azure Microsoft Quiz Answers

Get Microsoft Azure Data Fundamentals: Explore data analytics in Azure Microsoft Quiz Answers

The phenomenal growth in data in recent years is fueling digital transformation of businesses and other organizations by empowering fast and informed decision making through data analytics. Microsoft Azure provides multiple services that you can combine to build large-scale analytics solutions that leverage the latest technologies and techniques for data ingestion, storage, modeling, and visualization. This learning path helps you prepare for the Azure Data Fundamentals certification.

This learning path helps prepare you for Exam DP-900: Microsoft Azure Data Fundamentals.

Before starting this learning path, you should have a fundamental understanding of core data concepts, relational data, and non-relational data.

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Module 1: Explore fundamentals of large-scale data warehousing

About Module:

Organizations use modern data warehousing to build large scale data analytics solutions that generate insights and drive success. Microsoft Azure includes multiple technologies that you can combine to build a modern data warehousing solution.

In this module, you will learn how to:

  • Identify common elements of a modern data warehousing solution
  • Describe key features for data ingestion pipelines
  • Identify common types of analytical data store and related Azure services
  • Provision Azure Synapse Analytics and use it to ingest, process, and query data

Before starting this module, you should have a conceptual understanding of data and databases, and be familiar with Microsoft Azure services for data workloads such as Azure Storage, Azure SQL Database, and Azure Cosmos DB.

Quiz 1: Knowledge check

Q1. Which Azure services can you use to create a pipeline for data ingestion and processing?

  • Azure SQL Database and Azure Cosmos DB
  • Azure Synapse Analytics and Azure Data Factory
  • Azure HDInsight and Azure Databricks

Q2. What must you define to implement a pipeline that reads data from Azure Blob Storage?

  • A linked service for your Azure Blob Storage account
  • A dedicated SQL pool in your Azure Synapse Analytics workspace
  • An Azure HDInsight cluster in your subscription

Q3. Which open-source distributed processing engine does Azure Synapse Analytics include?

  • Apache Hadoop
  • Apache Spark
  • Apache Storm

Module 2: Explore fundamentals of real-time analytics

About Module:

Learn about the basics of stream processing, and the services in Microsoft Azure that you can use to implement real-time analytics solutions.

In this module, you’ll learn how to:

  • Compare batch and stream processing
  • Describe common elements of streaming data solutions
  • Describe features and capabilities of Azure Stream Analytics
  • Describe features and capabilities of Spark Structured Streaming on Azure
  • Describe features and capabilities of Azure Synapse Data Explorer

Before starting this module, you should have some conceptual understanding of modern data warehousing and analytics, and you should be familiar with Azure services for data workloads, including Azure Storage, Azure SQL Database, and Azure Synapse Analytics.

Quiz 1: Knowledge check

Q1. Which definition of stream processing is correct?

  • Data is processed continually as new data records arrives
  • Data is collected in a temporary store, and all records are processed together as a batch.
  • Data is incomplete and cannot be analyzed.

Q2. Which service would you use to continually capture data from an IoT Hub, aggregate it over temporal periods, and store results in Azure SQL Database?

  • Azure Cosmos DB
  • Azure Stream Analytics
  • Azure Storage

Q3. Which language would you use to query real-time log data in Azure Synapse Data Explorer?

  • SQL
  • Python
  • KQL

Module 3: Explore fundamentals of data visualization

About Module:

Learn the fundamental principles of analytical data modeling and data visualization, using Microsoft Power BI as a platform to explore these principles in action.

After completing this module, you will be able to:

  • Describe a high-level process for creating reporting solutions with Microsoft Power BI
  • Describe core principles of analytical data modeling
  • Identify common types of data visualization and their uses
  • Create an interactive report with Power BI Desktop

Quiz 1: Knowledge check

Q1. Which tool should you use to import data from multiple data sources and create a report?

  • Power BI Desktop
  • Power BI Phone App
  • Azure Data Factory

Q2. What should you define in your data model to enable drill-up/down analysis?

  • A measure
  • A hierarchy
  • A relationship

Q3. Which kind of visualization should you use to analyze pass rates for multiple exams over time?

  • A pie chart
  • A scatter plot
  • A line chart
Conclusion:

I hope this Microsoft Azure Data Fundamentals: Explore data analytics in Azure Microsoft Quiz Answers would be useful for you to learn something new from this problem. If it helped you then don’t forget to bookmark our site for more Coding Solutions.

This Problem is intended for audiences of all experiences who are interested in learning about Data Science in a business context; there are no prerequisites.

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