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Textbook: Textbook information Data Mining: Concepts and Techniques (Required) Jiawei Han, Micheline Kamber, Jian Pei Morgan Kaufmann; 3rd Edition; 2011 ISBN-10: 0123814790 ISBN-13: 978-0-12-381479-1 (Print) | 978-0-12-381480-7 (eBook) Assignment: Please consider the following questions for the discussions in the 4 areas. Note that there are several questions in each area, and while I recommend that you read all of the posts made in each area, there is no need for each student to provide answers to all of the questions. The requirement is one quality post in each of the 4 areas. At least 150 words per area. Please study each topic and make a good answer for each topic. Area 1: Data Warehouse: Basic Concepts (graded) Class, Please consider the following questions for the discussions in this area. Note that there are several questions below, and while I recommend that you read all of the posts made in this area, there is no need for each student to provide answers to all of the questions. Do not only reply to my post, please consider replying also to your classmates. The requirement is one quality post in this area. - What is a data warehouse? - What are some of the differences between operational database systems and data warehouses? - What is the rationale of constructing a separate data warehouse, when online analytical processing could be performed directly on operational databases? - What is a metadata repository and what are some of the elements it should contain? Area 2: Data Warehouse Modeling (graded) Class, Please consider the following questions for the discussions in this area. Note that there are several questions below, and while I recommend that you read all of the posts made in this area, there is no need for each student to provide answers to all of the questions. Do not only reply to my post, please consider replying also to your classmates. The requirement is one quality post in this area. - What do we understand by “multidimensional data model”? What is a “data cube”? - Explain in your own words the following concepts and use an example to illustrate your explanations: snowflake schema, fact constellation, and star schema. - What is a data cube measure? Any examples? - Explain and provide an example of an OLAP operation for multidimensional data. Area 3: Data Warehouse Design and Usage (graded) Class, Please consider the following questions for the discussions in this area. Note that there are several questions below, and while I recommend that you read all of the posts made in this area, there is no need for each student to provide answers to all of the questions. Do not only reply to my post, please consider replying also to your classmates. The requirement is one quality post in this area. - Discuss the steps associated to the design of a data warehouse. - Compare the waterfall and the spiral methods as methodologies to develop a data warehouse. - Compare/contrast the three main types of data warehouse usage: information processing, analytical processing, and data mining. - Please discuss the following statement given on page 155 of our textbook: “among the many different paradigms and architectures of data mining systems, multidimensional data mining is particularly important”. Area 4: Data Generalization (graded) Class, Please consider the following questions for the discussions in this area. Note that there are several questions below, and while I recommend that you read all of the posts made in this area, there is no need for each student to provide answers to all of the questions. Do not only reply to my post, please consider replying also to your classmates. The requirement is one quality post in this area. - Please discuss data generalization and some of the concepts associated to it. - What is attribute-oriented induction? - What is it understood by the “curse of dimensionality”? - Is data cube technology sufficient to accomplish all kinds of concept description tasks for large data sets?