introduction to data analytics coursera quiz answers week 2

The Data Ecosystem and Languages for Data Professionals

Practice Quiz

1. What data type is typically found in databases and spreadsheets?

  • Structured data
  • Social media content
  • Unstructured data
  • Semi-structured data

2. Which of these data sources is an example of semi-structured data?

  • Social media feeds
  • Network and web logs
  • Emails
  • Documents 

3. Which one of the provided file formats is commonly used by APIs and Web Services to return data?

  • Delimited file
  • XML
  • XLS
  • JSON

4. What is one example of the relational databases discussed in the video?

  • Spreadsheet 
  • Flat files
  • XML
  • SQL Server 

5. Which of the following languages is one of the most popular querying languages in use today?

  • SQL
  • R
  • Python
  • Java

Graded Quiz

6. In the data analyst’s ecosystem, languages are classified by type. What are shell and scripting languages most commonly used for?

  • Automating repetitive operational tasks
  • Manipulating data 
  • Building apps
  • Querying data 

7. Which of the following is an example of unstructured data?

  • Zipped files
  • Spreadsheets
  • Video and audio files
  • XML

8. Which one of these file formats is independent of software, hardware, and operating systems, and can be viewed the same way on any device?

  • PDF
  • XML
  • Delimited text file
  • XLSX

9. Which data source can return data in plain text, XML, HTML, or JSON among others?

  • Delimited text file
  • API
  • PDF 
  • XML

10. According to the video “Languages for Data Professionals,” which of the programming languages supports multiple programming paradigms, such as object-oriented, imperative, functional, and procedural, making it suitable for a wide variety of use cases?

  • Java
  • PowerShell 
  • Python
  • Unix/Linux Shell 

Understanding Data Repositories and Big Data Platforms

Practice Quiz

11. Structured Query Language, or SQL, is the standard querying language for what type of data repository?

  • NoSQL
  • Data lake
  • Flat Files

12. In use cases for RDBMS, what is one of the reasons that relational databases are so well suited for OLTP applications?

  • Support the ability to insert, update, or delete small amounts of data
  • Offer easy backup and restore options 
  • Allow you to make changes in the database even while a query is being executed
  • Minimize data redundancy

13. Which NoSQL database type stores each record and its associated data within a single document and also works well with Analytics platforms?

  • Graph-based
  • Document-based 
  • Key-value store
  • Column-based 

14. What type of data repository is used to isolate a subset of data for a particular business function, purpose, or community of users?

  • Data Warehouse
  • Data Mart
  • Data Lake
  • Data Pipeline

15. What does the attribute “Velocity” imply in the context of Big Data?

  • Scale of data 
  • Diversity of data 
  • Quality and origin of data
  • The speed at which data accumulates

16. Which of the Big Data processing tools provides distributed storage and processing of Big Data?

  • Hive
  • Hadoop
  • Spark
  • ETL

Graded Quiz

17. Data Marts and Data Warehouses have typically been relational, but the emergence of what technology has helped to let these be used for non-relational data?

  • NoSQL
  • SQL
  • ETL
  • Data Lake

18. What is one of the most significant advantages of an RDBMS?

  • Enforces a limit on the length of data fields
  • Requires source and destination tables to be identical for migrating data
  • Is ACID-Compliant 
  • Can store only structured data 

19. Which one of the NoSQL database types uses a graphical model to represent and store data, and is particularly useful for visualizing, analyzing, and finding connections between different pieces of data?

  • Document-based
  • Column-based 
  • Key value store
  • Graph-based

20. Which of the data repositories serves as a pool of raw data and stores large amounts of structured, semi-structured, and unstructured data in their native formats?

  • Relational Databases
  • Data Lakes
  • Data Marts
  • Data Warehouses

21. What does the attribute “Veracity” imply in the context of Big Data?

  • Diversity of the type and sources of data 
  • Diversity of the type and sources of data 
  • Accuracy and conformity of data to facts
  • Scale of data

22. Apache Spark is a general-purpose data processing engine designed to extract and process Big Data for a wide range of applications. What is one of its key use cases?

  • Consolidate data across the organization
  • Perform complex analytics in real-time 
  • Fast recovery from hardware failures 
  • Scalable and reliable Big Data storage

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