4.3.3 Module 4 Quiz – Embarking on Your Career in Data Analytics Exam Answers 100% 2023

  1. What is the role of a data analyst?

    • To query and process data, provide reports, summarize and visualize data.
    • To build and operationalize data pipelines for collecting and organizing data.
    • To apply statistics, machine learning, and analytic approaches to answer critical business questions.
    • To enter and validate data, to improve the reliability of the data being collected.
      Answers Explanation & Hints:

      The role of a data analyst is to query and process data, provide reports, summarize and visualize data to help organizations make data-driven decisions. They use statistical and analytical methods to extract insights and answer critical business questions.

  2. What is the role of a data scientist?

    • To query and process data, provide reports, summarize and visualize data.
    • To build and operationalize data pipelines for collecting and organizing data.
    • To apply statistics, machine learning, visualization techniques and analytic approaches to answer critical business questions.
    • To clean data from unstructured data.
      Answers Explanation & Hints:

      The role of a data scientist is to apply statistical, machine learning, visualization techniques, and analytic approaches to answer critical business questions. Data scientists are responsible for identifying and analyzing large and complex data sets, building predictive models, and generating insights to inform business decisions. They use a range of tools and techniques, including statistical analysis, data mining, machine learning algorithms, and data visualization, to extract meaningful insights from data. Data scientists are often involved in building and optimizing data pipelines for collecting and organizing data, as well as deploying models into production environments. While data cleaning is an important task, it is usually performed by data engineers or data entry specialists rather than data scientists.

  3. What tool is commonly used to showcase data analytic skills to a prospective employer?

    • Resume
    • Word document
    • Portfolio
    • Excel spreadsheet
      Answers Explanation & Hints:

      A portfolio is commonly used to showcase data analytic skills to a prospective employer. A portfolio is a collection of work samples that demonstrate a candidate’s skills, knowledge, and accomplishments. In the case of data analytics, a portfolio might include examples of data visualizations, statistical analyses, predictive models, and other relevant work. It can be presented in a variety of formats, including online platforms, PDFs, or physical copies. A portfolio can help a candidate stand out in a competitive job market by providing concrete evidence of their abilities and accomplishments.

  4. What is the role of a data engineer?

    • To query and process data, provide reports, summarize and visualize data.
    • To build and operationalize data pipelines for collecting and organizing data.
    • To apply statistics, machine learning, and analytic approaches to answer critical business questions using visualization techniques.
    • To enter and validate data, to improve the reliability of the data being collected.
      Answers Explanation & Hints:

      The role of a data engineer is to build and operationalize data pipelines for collecting and organizing data. Data engineers are responsible for designing, building, and maintaining the infrastructure that enables data scientists and analysts to access and analyze large volumes of data. This involves tasks such as designing and implementing data storage solutions, building and maintaining data processing pipelines, and ensuring the reliability and scalability of data systems. Data engineers also work closely with data scientists and analysts to understand their data requirements and ensure that the data is structured and organized in a way that enables efficient analysis.

  5. Which three are skills that are typical for an entry level data analyst position? (Choose three.)

    • Fast typing skills.
    • Ability to work alone.
    • Proficiency with spreadsheets.
    • Familiarity with visualization tools.
    • Proficiency with multiple programming languages.
    • Strong verbal and written communication skills.
      Answers Explanation & Hints:

      Proficiency with spreadsheets, familiarity with visualization tools, and strong verbal and written communication skills are skills that are typical for an entry-level data analyst position.

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