Introduction to Data Analytics Coursera Quiz Answers

Introduction to Data Analytics Week 01 Quiz Answers

Quiz: Graded Quiz Answers

Q1. A modern data ecosystem includes a network of continually evolving entities. It includes: 

• Data sources, enterprise data repository, business stakeholders, and tools, applications, and infrastructure to manage data
• Social media sources, data repositories, and APIs
• Data sources, databases, and programming languages
• Data providers, databases, and programming languages

Q2. Data Analysts work within the data ecosystem to:

• Build Machine Learning or Deep Learning models
• Develop and maintain data architectures
• Provide business intelligence solutions by monitoring data on different business functions
• Gather, clean, mine, and analyze data for deriving insights

Q3. When we analyze data in order to understand why an event took place, which of the four types of data analytics are we performing?

• Prescriptive Analysis
• Descriptive Analysis
• Predictive Analysis
• Diagnostic Analysis

Q4. The first step in the data analysis process is to gain an in-depth understanding of the problem and the desired outcome. What are you seeking answers to at this stage of the data analysis process?

• When you are and where you need to be
• The best tools for sourcing data
• What will be measured and how it will be measured
• The data you need 

Q5. From the provided list, select the three emerging technologies that are shaping today’s data ecosystem.

• Cloud Computing, Internet of Things, and Dashboarding
• Machine Language, Cloud Computing, and Internet of Things
• Big Data, Internet of Things, and Dashboarding
• Cloud Computing, Machine Learning, and Big Data

Introduction to Data Analytics Week 02 Quiz Answers

Quiz: Graded Quiz Answers

Q1. 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 
• Querying data 
• Building apps 

Q2. Which of the following is an example of unstructured data? 

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

Q3. Which one of these file formats is independent of software, hardware, and operating systems, and can be viewed the same way on any device?

• Delimited text file
• XLSX
• PDF
• XML

Q4. Which data source can return data in plain text, XML, HTML, or JSON among others? 

• XML 
• Delimited text file 
• API
• PDF 

Q5. 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? 

• PowerShell 
• Python
• Java
• Unix/Linux Shell 

Introduction to Data Analytics Week 03 Quiz Answers

Quiz: Graded Quiz Answers

Q1. What are some of the steps in the process of “Identifying Data”? (Select all that apply)

•  Define the checkpoints 
•  Define a plan for collecting data 
• Determine the visualization tools that you will use
•  Determine the information you want to collect 

Q2. What type of data refers to information obtained directly from the source?

•  Secondary data 
•  Primary data 
•  Sensor data 
•  Third-party data 

Q3. Web scraping is used to extract what type of data? 

• Data from news sites and NoSQL databases
• Text, videos, and images
• Text, videos, and data from relational databases
• Images, videos, and data from NoSQL databases

Q4. Data obtained from an organization’s internal CRM, HR, and workflow applications is classified as:

• Copyright-free data
• Secondary data
• Third-party data
• Primary data

Q5. Which of the provided options offers simple commands to specify what is to be retrieved from a relational database?

• RSS Feed
• API
• SQL
• Web Scraping

Introduction to Data Analytics Week 04 Quiz Answers

Quiz: Graded Quiz Answers

Q1. What is a branch of mathematics dealing with the collection, analysis, interpretation, and presentation of numerical or quantitative data?

• Algebra
• Calculus
• Statistics
• Pie

Q2. Data Mining is defined as the process of:

• Preparing raw data for analysis
• Filtering data based on pre-defined criteria
• Identifying errors in data
• Extracting knowledge from data

Q3. What type of data mining operations was R specifically built to handle?

• Classification of data 
• Filtering
• Calculating mean, median, and mode
• Sorting

Q4. When you’re calculating the middle value of a data field in a data set, what are you really calculating?

• Mean
• Average
• Mode
• Median

Q5. What is the general tendency of a set of data to change over time called?

• Anomaly
• Trend
• Variation
• Pattern

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