The post is about Quiz Data Analytics. There are 20 multiple-choice type questions related to “The Data Ecosystem and Languages for Data Professionals” covering the Languages related to the work of data professionals such as type of data, format of data, audience, query languages, programming languages, and shell scripting. Let us start with the Quiz Data Analytics Questions now.
Online Quiz Data Analytics with Answers
Quiz Data Analytics with Answers
- Which file format is independent of software, hardware, and operating systems and can be viewed the same way on any device?
- Which data source can return data in plain text, XML, HTML, or JSON?
- What is the next step must you perform after you download a dataset file from a URL?
- “A presentation is not a data dump”. What is the one thing you would do to ensure your presentation is not a data dump?
- What can you do to help your audience trust you?
- What data type is data from emails, XML, zipped files, binary executables, and TCP/IP protocols?
- Why is it important to understand the underlying data that was used to generate a data set in the context of reliability?
- Why is it important to understand the information needs of your audience?
- 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?
- What are the requirements for data to be reliable?
- What type of data is produced by wearable devices, smart buildings, and medical devices?
- What type of data is semi-structured and has some organizational properties but not a rigid schema?
- What is one of the common structural transformations used for combining data from one or more tables?
- What does a typical data-wrangling workflow include?
- What is one of the steps in a typical data-cleaning workflow?
- When applying for a data science position, you may be tested on basic linear algebra and multivariable calculus.
- Most data visualization solutions provide users with a wide range of opportunities for data analytics, interpretation, exploration, and application.