Analytics projects that overlook data-related tasks (some of the most critical steps) often end up with the wrong answer for the right problem, and these unintentionally created, seemingly good answers could lead to inaccurate and untimely decisions. Some of the most common metrics that make for analytics-ready data were mentioned. Choose three of these metrics and discuss them succinctly using resources. Your references should not be less than four in total.
I am aware that all students have a Grammarly account. I, therefore, request you all to use Grammarly to check your paper before you upload to iLearn, failing to do so will cause you to lose some points. The essence of doing this is to ensure that your paper is free from grammatical errors, conjugation, and spellings.
Additionally, post some examples or find a related topic on the Internet.
Reference: Sharda, R., Delen, Dursun, and Turban, E. (2020). Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support. 11th Edition. By PEARSON Education. Inc. ISBN-13: 978-0-13-519201-6