I WILL PROVIDE LOGIN INFO TO ANY SOFTWARE UPON CONTRACT ACCEPTANCE. Assignment ?3 Decision Tree model development using Cognos Analytics Submission via LEO. Grading criteria Submitted assignments will be graded for (a) content, (b) document quality (i.e. formatting, following guidelines, pleasant to read, etc.), and timeliness of submission. Assignments submitted late will be deducted 5 points for each day it is late. Activities 1. Login to your Cognos Analytics account and navigate to Team Content -> Data 610 Data for Assignments -> Assignment 3 and 4 in Figure 1. 2. You will see 6 datasets in the folder. Select one dataset and save a copy of the file to my content. I HAVE CHOSEN LAPTOP SALES DATA SET. 3. Save a copy of the data to My Content and create a data module. 4. Discuss the selected dataset in the paper. Include the number of cases, description of the inputs, description of the variables that could be used to develop predictive models, etc. (NOTE: predictive models are developed better with larger data sets that have many cases and possible inputs from which to select.) 5. Develop prediction models: a) Use the data module in step 3 as a data source to develop complete Decision Tree prediction models. There should be at least two models developed: ? Be sure to specify which variable is being predicted and which variables are to be used to predict the outcomes. ? Discuss in detail the models and why the target variable is important to predict. b) For each of the models created: ? Drill down into the results and interpret what the results indicate about the relationship between the input variables and the target variable. Which variables are the strongest predictors? What is the single best predictor variable? What combination of variables seems to give the best answer? Why? ? Provide the rules found and discuss how the use of these rules would be useful in your organization. How would you implement the use of a rule-based approach? How would the models be accepted? ? Discuss the Sunburst diagram. What additional information and/or insights does it provide? ? Create some other combinations of variables. See if you can derive a more accurate model, or a model that is equally accurate but simpler (i.e., has fewer variables). Consider how to improve the model (e.g., removing extraneous variables, improving data quality, etc.) Discuss your findings in detail. Consider creating additional variables that might add value to the model. Support your findings. Important We may add calculations, hierarchies, filters, etc. in the data module and/or in the exploration file. Any updates to the data module will be available in all explorations, dashboards, and stories where the data module is used as a source. Any data filters, calculations, etc. defined in the exploration file are unavailable outside the file where they are defined. Submission Submit a single document conforming to the guidelines and standards outlined below. Document format: limited to 7 pages (excluding title page, references, and appendix), Double-spaced, 12 point Times New Roman font, 1 margins, Bottom-right page numbering. Note: Submitted report must be either in MS Word or PDF format and titled: Assignment3_LastName. Only one document will be allowed to be submitted. Content (note that the document must have clearly marked sections for the items listed below) 1) Title page (1 page limit): course number and term, assignment number and project title, student name and contact information, instructors name. Format it so it looks pleasant and presentable. Follow formatting guidelines above. 2) Introduction. Provide a brief outline of the dataset you are using for this assignment. Briefly explain the content of the data, to include a description of the variables in the data sets, the number of cases, etc. Include a screenshot of the data (not all, but partial as far as all relevant variables are visible). Include any data cleansing and/or preparation you did. 3) Develop and discuss at least two predictive models and the results. Include any insights gained from drilling down on the models. Discuss the top five best rules found in the analysis. Discuss how the rules developed from the decision tree help with the decision. What does the Sunburst view show that is insightful? 4) Discussion of additional models developed. Include a comparison of developed models you created. What improvements did you make? How well did they work out? 5) Outline and discuss at least one area in your organization (or an organization with which you are familiar) where this rules-based approach would be beneficial and how it would be implemented. 6) References (1 page limit): List all references in APA format used in preparing this report. It is strongly recommended to use outside knowledge in setting-up the analysis or discussing the results where possible. 7) Appendix (6 page limit): Include any appropriate workbooks, screenshots (figures, tables, diagrams) used in this assignment. Be sure to include complete and legible decision trees developed for all models; be sure to include a complete set of the rules developed from the models. Make sure all tables, figures, or diagrams are properly numbered and titled. For example, Table 1. Model Results. Make sure all tables or figures or diagrams are easily readable and visually presentable. General guidance Assignments that: 1) adequately address all required tasks; 2) are submitted on time; 3) are properly formatted (APA format for references, no typos or misspelled words, no grammar errors, cover page, etc.) will receive a grade of B (80-89, depending on content).