Introduction to data analytics on Azure Microsoft Quiz Answers

Get Introduction to data analytics on Azure Microsoft Quiz Answers

Explore Azure data services, concepts of data analytics, and what you need to implement modern analytics at scale. This learning path helps you prepare for the Azure Enterprise Data Analyst Certification.

This learning path helps prepare you for Exam DP-500: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI.

Prerequisites:

• You should be familiar with basic data concepts and terminology.

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Module 1: Explore Azure data services for modern analytics

Understand analytics solutions in the Azure data ecosystem. Explore the architecture of a scalable analytics solution to meet business needs.

Learning objectives:

After completing this module, you will be able to:

• Describe the Azure data ecosystem for analytics

Prerequisites:

• You should be familiar with basic data concepts and terminology.

Quiz 1: Knowledge check

Q1. What type of data is best suited for batch processing?

• IoT gas sensor data that monitors and detects the presence of toxic or hazardous gasses.
• Real-time personalized advertising data.
• Daily sales report data.

Q2. What is one advantage of using Power BI over a Synapse notebook for data visualization?

• There is no advantage, Power BI and Azure Synapse Analytics are comparable for data visualization
• Power BI was designed for distribution of data products outside of the data team.
• Power BI displays simple visualizations compared to Synapse notebooks.

Module 2: Understand concepts of data analytics

Explore key concepts of data analytics, including types of analytics, data, and storage. Explore the analytics process and tools used to discover insights.

Learning objectives:

After completing this module, you will be able to:

• Describe types of data analytics
• Understand the data analytics process

Prerequisites:

• You should be familiar with basic data concepts and terminology.

Quiz 1: Knowledge check

Q1. Which of the following is an example of descriptive analytics?

• A monthly sales report looking at sales data over the last year
• A social media algorithm that recommends curated content
• An annual HR report that forecasts predicted attrition for the next year

Q2. What are the first three steps in the data analytics process?

• Data exploration, data analysis, and deploy analytics solution
• Data analysis, deploy analytics solution, and request feedback
• Requirements gathering, data ingestion and processing, and data exploration

Q3. Why is it important to understand the difference between structured and unstructured data?

• There is no difference between structured and unstructured data
• Understanding the difference can determine where data should be stored and what kind of analysis is most appropriate
• Understanding the difference will determine if the business requirements have been met

Module 3: Explore data analytics at scale

Describe data analytics at scale and understand the roles of a data team. Learn about the responsibilities of an enterprise data analyst and what tools are available to build scalable solutions.

Learning objectives:

After completing this module, you will be able to:

• Explore data job roles in analytics
• Understand tools for scaling analytics solutions

Prerequisites:

• You should be familiar with basic data concepts and terminology.

Quiz 1: Knowledge check

Q1. Which of the following tasks are completed by a data analyst?

• Build monthly sales reports and gather feedback from the business on how reports are being used.
• Design, implement, and maintain operational aspects of on-premises and cloud-based database systems.
• Manage and secure the flow of structured and unstructured data from multiple sources into analytical data storage.

Q2. What Microsoft tools do data analysts use for enterprise-scale analytics solutions?

• Azure Machine Learning and Azure Cosmos DB.
• Microsoft Excel.
• Azure Synapse Analytics and Microsoft Power BI

Q3. What people focused strategies can help an organization achieve analytics at scale?

• Azure Synapse Analytics and Microsoft Power BI can help achieve analytics at scale in an organization.
• Building a data culture, establishing a Center of Excellence, and creating a community of practice.
• Achieving analytics at scale should be technology focused rather than people focused.Check your answers

Conclusion:

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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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