In this hypothetical case, you have a database with the x, y coordinates and names of all nearby restaurants. The following enquiries are required: If the location is suitable for a restaurant, the investigation examines. Why is B-tree indexing better than R-tree? Why?

Please do the normalisation for attached ERD in 1NF, 2NF, 3NF by showing the new table getting from it. The detail hire table is resolving the many to many relationship of to and hire tables

Explain the concept of self-balancing binary trees and provide an in-depth analysis of B-trees and their role in database management systems.

Please please do this manually  a.What is the distance between the two farthest members? (max or complete link) (round to four decimal places here, and next 2 problems); b. What is the distance between the two closest members? (min or single link);c. What is the average distance between all pairs? d. What is the center distance between two clusters? e. Among all three distances above, which one is robust to noise? Answer either “complete”, “single”, “average”, and "center"

When we buy a packaged data model, we receive whatever element we obtain as part of the deal.

2. Examine the dendrogram: How many clusters seem reasonable for describing the data?

Consider the transaction database in the table below: TID items_bought 1 {a, b, c, d} 2 {b, c, e, f} 3 {a, d, e, f} 4 {a, e, f} 5 {b, d, f} Show the prefix-based enumeration tree of frequent itemsets, for the data set of the table above at an absolute minimum support level of 2. Assume a lexicographic ordering of a, b, c, d, e, f.

In piecewise regression, what are breakpoints?

From the instructor relation of the large university database, find the number of professors in each of the department of the university.

Which statement best describes k-means cluster analysis?   Question 9 options:   It is the process of organizing observations into distinct groups based on a measure of similarity or dissimilarity.   It is the process of agglomerating observations into a series of nested groups based on a measure of similarity or dissimilarity.   It is the process of reducing the number of variables to consider in data-mining.    It is the process of estimating the value of a continuous outcome variable.