Section 2.2 Review Questions How do you describe the importance of data in analytics? Can we think of analytics without data? Data is the main ingred ient in all forms of analytics. You cannot have analytics without data Considering the new and broad definition of business analytics, what are the main inputs and outputs to the analytics continuum? Because of the broader definition of business analytics, almost any data from almost any source can be considered an input. In the same way, after analytics has been performed output can take a wide variety of forms depending on the specific business purpos Where does the data for business analytics come from? Data can come from a wide variety of locations. Examples can include business processes and systems, the Internet and social media, and machines or the Internet of th 4. In your opinion, what are the top three data-related challenges for better analytics? Opinions will vary, but examples of challenges include data reliability, accuracy, accessibility, security, richness, consistency, timeliness, granularity, valid ity, and elevance 5 What are the most common metrics that make for analytics-ready data? It must be relevant to the problem at hand and meet the quality/quantity requirements. It also has to have a certain data structure in place with key field s/variables with properly normalized values and conform to organizational definitions Section 2.3 Review Questions 1. What is data? how does data differ from information and knowledge? Data refers to a collection of facts usually obtained as the result of experiments, observations, transactions, or experiences. Data may consist of numbers, letters, words. images, voice recordings and so on. as measurements of a set of variables Data is a raw commod ity and does not become information or knowledge until after it is processed Copyright C2018 Pearson Education, Inc.4 Copyright © 2018Pearson Education, Inc. Section 2.2 Review Questions 1. How do you describe the importance of data in analytics? Can we think of analytics without data? Data is the main ingredient in all forms of analytics. You cannot have analytics without data. 2. Considering the new and broad definition of business analytics, what are the main inputs and outputs to the analytics continuum? Because of the broader definition of business analytics, almost any data from almost any source can be considered an input. In the same way, after analytics has been performed output can take a wide variety of forms depending on the specific business purpose. 3. Where does the data for business analytics come from? Data can come from a wide variety of locations. Examples can include business processes and systems, the Internet and social media, and machines or the Internet of Things. 4. In your opinion, what are the top three data-related challenges for better analytics? Opinions will vary, but examples of challenges include data reliability, accuracy, accessibility, security, richness, consistency, timeliness, granularity, validity, and relevance. 5. What are the most common metrics that make for analytics-ready data? It must be relevant to the problem at hand and meet the quality/quantity requirements. It also has to have a certain data structure in place with key fields/variables with properly normalized values and conform to organizational definitions. Section 2.3 Review Questions 1. What is data? How does data differ from information and knowledge? Data refers to a collection of facts usually obtained as the result of experiments, observations, transactions, or experiences. Data may consist of numbers, letters, words, images, voice recordings, and so on, as measurements of a set of variables. Data is a raw commodity and does not become information or knowledge until after it is processed