Hello, I need help responding to my classmates for a discussion question.

The discussion question is Describe three situations that can be good candidates for denormalization and justify your selections?

I don't know what to respond to them. I will post the responses below.

I am not looking for an answer to the discussion question. I am looking for help on what to respond to the the posts that my classmates made.

Below are the posts that my classmates made. I am required to reply to them by providing feedback on my thoughts about their post.

Classmate#1

The denormalization process reduces the number of joins in the query process. When the number of joins is reduced, the data acquisition process is sped up. One of the candidates for denormalization are 1:1 relationships. The 1:1 relationship of data is described as pulling two correlating sets of data together. The 1:1 data relationship is a good candidate for denormalization as two sets of data can be connected with one another. Another good candidate for denormalization is the 1:N relationship. This relationship is set up as parent entities and child entities. For example, a customer is the parent and the order is the child, and the queries that need customer information can be pulled from the order data set. The third denormalization method would be a data modeling technique called star schema design. The star schema is made up of tables that describe business entities and events and observations. The dimension tables include information like products, people, places, etc. The fact tables include observations and events like sales orders exchange rates, etc. Using this method can give different dimensions to data sets.

Classmate# 2

1: To enhance query performance (B. & B., 2020)

Adding redundancy to a database by copying values between parent and child tables Reduces the number of joins required for a query 2: To make a database more convenient to manage (B. & B., 2020)

Having calculated values to prevent having to do them when requested, slowing down query execution Once generated and added to the tables, programmers can create their own reports and queries 3: To facilitate and accelerate reporting (B. & B., 2020)

Live data is time-consuming and can negatively impact overall system performance To save time you could maintain a year-to-date summary table storing user details.