Introduction to Data Analytics | Coursera Quiz Answers

Introduction to Data Analytics | Coursera IBM

Embark on an exciting journey into the world of data analytics with IBM's Introduction to Data Analytics course on Coursera. This comprehensive program covers essential topics such as data collection, analysis, and visualization, equipping you with the skills to make data-driven decisions. Whether you're just starting or looking to enhance your existing knowledge, this course offers valuable insights and practical applications. Struggling with the coursework? Don’t worry! Our vibrant community is here to help you with answers and support. Join us today and take the first step towards becoming a data analytics pro!

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Graded Quiz: Modern Data Ecosystem and the Role of Data Analytics

1. 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 
• Data providers, databases, and programming languages 
• Data sources, databases, and programming languages 
• Social media sources, data repositories, and APIs 

2. Data Analysts work within the data ecosystem to:

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

3. 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
• Diagnostic Analysis
• Predictive Analysis

4. 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?

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

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

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

Graded Quiz: The Data Analyst Role

 1. Why is proficiency in Statistics an important skill for a Data Analyst?

• For acquiring data from multiple sources
• For creating queries to extract required data 
• For creating project documentation 
• For identifying patterns and correlations in data 

2. Which of these is one of the soft skills required to be a successful Data Analyst?

• Work collaboratively with cross-functional teams 
• Integrate data coming from multiple sources 
• Filter, clean, and standardize data 
• Prepare reports and dashboards

3. Which of the data analyst functional skills helps research and interpret data, theorize, and make forecasts?

• Probing skills 
• Proficiency in Statistics
• Problem-solving skills 
• Analytical skills 

4. In “A day in the life of a Data Analyst”, what according to Sivaram Jaladi forms a large part of a Data Analyst’s job?

• Generating hypotheses
• Creating a report
• Interacting with stakeholders 
• Cleaning and preparing data 

5. In “A day in the life of a Data Analyst”, what are some of the data points that were useful in analyzing the use case. (Select all that apply)

• Age and education details of complainants
• Average billing amount of complainants
• Serial number of the meters
• Employment history of the complainants

Graded Quiz: The Data Ecosystem and Languages for Data Professionals

1. 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 

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

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

3. 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
• XLSX
• XML
• Delimited text file

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

• API
• Delimited text file 
• XML 
• PDF 

5. 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  
• Unix/Linux Shell   
• Python
• PowerShell 

Graded Quiz: Understanding Data Repositories and Big Data Platforms

1. 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?

• SQL
• NoSQL
• Data Lake
• ETL

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

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

3. 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? 

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

4. 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?   

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

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

• Scale of data
• Accuracy and conformity of data to facts
• The speed at which data accumulates
• Diversity of the type and sources of data 

6. 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
• Fast recovery from hardware failures   
• Perform complex analytics in real-time 
• Scalable and reliable Big Data storage

Graded Quiz: Gathering Data

1. 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 information you want to collect
• Determine the visualization tools that you will use

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

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

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

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

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

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

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

• Web Scraping
• API
• SQL
• RSS Feed

Graded Quiz: Wrangling Data

1. What does a typical data wrangling workflow include?

• Using mathematical techniques to identify correlations in data
• Recognizing patterns
• Predicting probabilities
• Validating the quality of the transformed data

2. OpenRefine is an open-source tool that allows you to:

• Enforces applicable data governance policies automatically
• Transform data into a variety of formats such as TSV, CSV, XLS, XML, and JSON
• Automatically detect schemas, data types, and anomalies
• Use add-ins such as Microsoft Power Query to identify issues and clean data

3. What is one of the steps in a typical data cleaning workflow?

• Inspecting data to detect issues and errors
• Establishing relationships between data events
• Building classification models
• Clustering data

4. When you’re combining rows of data from multiple source tables into a single table, what kind of data transformation are you performing?

• Joins
• Unions
• Normalization
• Denormalization

5. When you detect a value in your data set that is vastly different from other observations in the same data set, what would you report that as?

• Syntax error
• Irrelevant data
• Outlier
• Missing value

Graded Quiz: Analyzing and Mining Data

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

• Algebra
• Statistics
• Pie
• Calculus

2. Data Mining is defined as the process of:

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

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

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

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

• Average
• Mean
• Mode
• Median

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

• Trend
• Anomaly
• Variation
• Pattern

Graded Quiz: Communicating Data Analysis Findings

1. "A presentation is not a data dump”. What is the one thing you would do to ensure your presentation is not a data dump?

• Include only that information as is needed to address the business problem
• Deliver the findings in a single slide
• Not include facts and figures in the presentation
• Not use visuals in the presentation

2. What is the discipline of communicating information through the use of visual elements?

• Data type conversion
• Data profiling
• Data visualization
• Data regression

3. Matplotlib is a widely used Python data visualization library.

• True
• False

4. What is the goal of Data Visualization?

• Make collaboration easy
• Make the presentation look attractive
• Make information easy to comprehend, interpret, and retain
• Establish trust in the audience

5. What can you do to help your audience trust you?

• Hand them copies of the data sets you have used for analysis
• Share the detailed documentation of every aspect of your project so they can verify all details
• Make your presentation look good
• Share your data sources, hypotheses, and validations

Graded Quiz: Opportunities and Learning Paths

1. Which of the following statement describes Data Analyst Specialist Roles?

• Analysts who advance technical, statistical, and analytical skills, over time, to expert levels
• Analysts who can work with Machine and Deep Learning models
• Analysts who specialize in specific fields like HR, Sales, and Finance
• Analysts who specialize in data lakes and data repositories

2. A Principal Data Analyst is responsible for:

• Having expertise in all tools and technologies used in data analytics
• Being well-versed in Big Data processing tools
• Establishing processes in the team
• Being a domain specialist

3. Job roles such as Project Managers, Marketing Managers, and HR Managers, can achieve greater efficiency and effectiveness in their current roles by acquiring data analysis skills, and are therefore known as analytics-enabled job roles.

• True
• False

4. Which of these is essential for getting started and growing as a Data Analyst?

• A degree in Computer Science
• Domain specialization
• Love for numbers, a curious mind, and openness to learn
• A degree in Statistics

5. What Data Analysis roles may be best suited for people with little or no technical training?

• Big Data Engineer
• Data Analyst
• Data Scientist
• Functional Analyst

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