Course Name: ITG 310 Data warehousing Assessment Type: Individual Assignment Assessment Title: Data warehousing Assessment Details and Submission Guidelines Purpose of the This assignment is designed to assess students' knowledge and skills related to the assessment (with following learning outcomes: Course Learning Question cover CLO3 Outcome 1. Apply data acquisition, planning, centralization, distribution, performance Mapping) and presentation to build a data warehouse Weight 10% of the total assessments Total Marks 100 Word limit 1500 words (6 to 8 Pages) Due Date Week 10, Tuesday 28 April 2021 - submit your report on Google Classroom and Turnitin Submission All work must be submitted on Google Classroom and Turnitin website by the due Guidelines date along with a Title Page. The Assignment must be in MS Word format, 1.5 spacing, 11-pt Calibri (Body) font and 2.54 cm margins on all four sides of your page with appropriate section headings. Reference sources must be cited in the text of the report and listed appropriately at the end in a reference list using IEEE or Harvard referencing style. You can use the below library resources available to our students: ACM DIGITAL LIBRARY- https://dl.acm.org/ IEEE Pick 5 - https://www.computer.org/csdl/home . 1) IEEE Intelligent systems 2) IEEE Transactions on software engineering 3) IEEE Security and privacy 4) IEEE Software 5) IEEE Transactions on pattern analysis and machine intelligence Market basket analysis application of association analysis Assignment Description: 10 points Question cover CLO3 . 0 . Write a report with snapshot, all process step by steps Different students bring different experiences to the assignment; feel free to spend more time on one question or the other according to your background. This assignment will be graded on the quality of your discussion, good English writing skills, and evidence that you read the case study. Check spelling, grammar and punctuation before submitting. For the assignment use the use the Riped Miner style in explaining support and confidence percentages in this Assignment, the classic example of shopping basket analysis was used. For this Assignment, you will do a shopping basket association rule analysis. Complete the following steps: Using the Internet, locate a sample shopping basket data set. Search terms such as association rule data set or shopping basket data set will yield a number of downloadable examples. With a little effort, you will be able to find a suitable example. Marks 20 Marking criteria: Marking criteria is shown in the following table. Marks allocated as follows: Note: The marking criteria varies for each Assignment Sections to be included Description of the section in the report Question 1 1. If necessary, convert your data set to CSV format or excel format and import it into your Rapid Miner repository. Give it a descriptive name and drag it into a new process window. As necessary, conduct your Data Understanding and Data Preparation activities on your data Question 2 2. As necessary, conduct your Data Understanding and Data Preparation activities on your data set. Ensure that all of your variables have consistent data and that their data types are appropriate for the FP-Growth operator. 20 Course Name: ITG 310 Data warehousing Assessment Type: Individual Assignment Assessment Title: Data warehousing Assessment Details and Submission Guidelines Purpose of the This assignment is designed to assess students' knowledge and skills related to the assessment (with following learning outcomes: Course Learning Question cover CLO3 Outcome 1. Apply data acquisition, planning, centralization, distribution, performance Mapping) and presentation to build a data warehouse Weight 10% of the total assessments Total Marks 100 Word limit 1500 words (6 to 8 Pages) Due Date Week 10, Tuesday 28 April 2021 - submit your report on Google Classroom and Turnitin Submission All work must be submitted on Google Classroom and Turnitin website by the due Guidelines date along with a Title Page. The Assignment must be in MS Word format, 1.5 spacing, 11-pt Calibri (Body) font and 2.54 cm margins on all four sides of your page with appropriate section headings. Reference sources must be cited in the text of the report and listed appropriately at the end in a reference list using IEEE or Harvard referencing style. You can use the below library resources available to our students: ACM DIGITAL LIBRARY- https://dl.acm.org/ IEEE Pick 5 - https://www.computer.org/csdl/home . 1) IEEE Intelligent systems 2) IEEE Transactions on software engineering 3) IEEE Security and privacy 4) IEEE Software 5) IEEE Transactions on pattern analysis and machine intelligence Market basket analysis application of association analysis Assignment Description: 10 points Question cover CLO3 . 0 . Write a report with snapshot, all process step by steps Different students bring different experiences to the assignment; feel free to spend more time on one question or the other according to your background. This assignment will be graded on the quality of your discussion, good English writing skills, and evidence that you read the case study. Check spelling, grammar and punctuation before submitting. For the assignment use the use the Riped Miner style in explaining support and confidence percentages in this Assignment, the classic example of shopping basket analysis was used. For this Assignment, you will do a shopping basket association rule analysis. Complete the following steps: Using the Internet, locate a sample shopping basket data set. Search terms such as association rule data set or shopping basket data set will yield a number of downloadable examples. With a little effort, you will be able to find a suitable example. Marks 20 Marking criteria: Marking criteria is shown in the following table. Marks allocated as follows: Note: The marking criteria varies for each Assignment Sections to be included Description of the section in the report Question 1 1. If necessary, convert your data set to CSV format or excel format and import it into your Rapid Miner repository. Give it a descriptive name and drag it into a new process window. As necessary, conduct your Data Understanding and Data Preparation activities on your data Question 2 2. As necessary, conduct your Data Understanding and Data Preparation activities on your data set. Ensure that all of your variables have consistent data and that their data types are appropriate for the FP-Growth operator. 20