Description Possible Marks and Wtg(%) Word Count Due date Assignment 2 Written Practical Report 100 marks 15% Weighting 2000 26/04/17 The key frameworks and concepts covered in modules 1–5 are particularly relevant for this assignment. Assignment 2 relates to the specific course learning objectives 1, 2 and 4 and associated MBA program learning goals and skills: Global Content, Problem solving, Critical thinking, and Written Communication at level 3: 1. demonstrate applied knowledge of people, markets, finances, technology and management in a global context of business intelligence practice (data warehouse design, data mining process, data visualisation and performance management) and resulting organisational change and how these apply to implementation of business intelligence in organisation systems and business processes 2. identify and solve complex organisational problems creatively and practically through the use of business intelligence and critically reflect on how evidence based decision making and sustainable business performance management can effectively address real world problems 4. demonstrate the ability to communicate effectively in a clear and concise manner in written report style for senior management with correct and appropriate acknowledgment of main ideas presented and discussed. Note you must use RapidMiner Studio for Task 2 and Tableau Desktop for Task 3 in this Assignment 2. Failure to do so may result in Task 2 and/or 3 not being marked and zero marks awarded. Note carefully University policy on Academic Misconduct such as plagiarism, collusion and cheating. If any of these occur they will be found and dealt with by the USQ Academic Integrity Procedures. If proven, Academic Misconduct may result in failure of an individual assessment, the entire course or exclusion from a University program or programs.Assignment 2 consists of three main tasks and a number of sub tasks Task 1 Data Driven Decision Making (Worth 40 Marks) Data driven decision-making – (3D) - Increasingly organisations are looking to make decisions that are based on the evidence of real data. Data analytics toolsets are evolving rapidly and many organisations have invested heavily in information architecture so that they have the capability to move transactional data and external data into data warehouses and provide end-users with specific data analytics software applications to support evidence based (data driven) decision making. However, many organisations are still struggling to make the transition to a data driven decision making paradigm. Your task as the Data Analytics Lead in XYZ company is to conduct a review of the relevant literature regarding data driven decision-making (3D) and prepare a strategic briefing report of about 1350 words for the Chief Executive Officer of XYZ company on key aspects of data driven decision making as outlined below: Task 1.1) Identify from the existing literature and discuss the relevant decision making theories and frameworks which would inform a deeper understanding of the decision making process in organisations (about 700 words) Task 1.2) Provide a comprehensive definition of data driven decision making and explain briefly how your definition has been informed by specific literature on data driven decisionmaking (about 150 words) Task 1.3) Based on an understanding of how decisions are made in organisations, discuss how changing organisational culture would be important for Company XYZ to successfully make the transition to a data driven decision making paradigm (about 500 words)Task 2 Exploratory Data Analysis and Decision Tree Analysis (Worth 25 Marks) Task 2.1) Conduct an exploratory data analysis of the patient-health.csv data set using the RapidMiner Studio data mining tool. Summarise the findings of your exploratory data analysis in terms of describing key characteristics of each of the variables in the patienthealth.csv data set such as maximum, minimum values, average, standard deviation, most frequent values (mode), missing values and invalid values etc and relationships with other variables if relevant in a table named Table 2.1 Results of Exploratory Data Analysis for the patient-health.csv Data Set. Hint: The Statistics Tab and the Chart Tab in RapidMiner provide descriptive statistical information and useful charts like Barcharts, Scatterplots etc. You might also like to look at running some correlations and chi square tests to indicate which variables you consider to be the top five key variables and which contribute most to determining whether a patient is healthy. Note in completing Task 2.1 you will find it useful to refer to the data dictionary for the patient-health.csv data set provided in this document which defines each of the variables in terms of their data type and range of values. Briefly discuss the key results of your exploratory data analysis presented in Table 2.1 and the rationale for why you have selected your five top variables for predicting Patient Health. (About 250 words) Task 2.2) Build a Decision Tree model for predicting Patient Health using RapidMiner and an appropriate set of data mining operators and a reduced patient-health.csv data set determined by your exploratory data analysis in Task 2.1. Provide these outputs from RapidMiner (1) Final Decision Tree Model process, (2) Final Decision Tree diagram, and (3) Decision Tree rules for Task 2.2. Briefly describe your final Decision Tree Model Process, and discuss the results of the Final Decision Tree Model drawing on the key outputs (Decision Tree Diagram, Decision Tree Rules) for predicting Patient Health and relevant supporting literature on the interpretation of decision trees (About 250 words). Include all appropriate RapidMiner outputs such as RapidMiner Processes, Graphs and Tables that support the key aspects of your exploratory data analysis and decision tree model analysis of the data set in your Assignment 2 report. Note you need export these outputs from RapidMiner using the File/Print/Export Image option and where relevant include in Task 2 and/or in Appendix A of the Assignment 2 report. Table 1 Patient Health Data Set Data Dictionary Variable Name Type and description of variable Range of values 1. Patient_id Integer Patient Id Range 1 to 20,000 2. genhealth Polynominal, Health Rating of each patient Poor, Fair, Good, Very Good, Excellent 3. exerany Integer, does the patient exercise? 1 or 0 4. hlthplan Integer, Health insurance plan? 1 or 0 5. smoke100 Integer, Smoker? 1 or 0 6. height Integer, height in inches of patient Height range in inches 7. weight Integer, weight in pounds of each patient? Weight range in pounds 8. wtdesire Integer, desired weight of each patient can be used to calculate if a patient is overweight etc Desired weight of each patient in pounds 9. age Integer Age of each patient 10. gender Polynominal, Gender of each patient M = Male; F = FemaleTask 3 Reports using Tableau Desktop (Worth 25 Marks) The following web site was used to construct a list of people who died while climbing Mount Everest. https://en.wikipedia.org/wiki/List_of_people_who_died_climbing_Mount_Everest contained in MtEverestDeaths.xlsx. This data set contains the following variables, note there are missing values in this data set. Variable Name Type and description of variable Range of values No_Deaths Integer running count of deaths recorded in climbing Mt Everest Name Character String, Name of person who died on Mt Everest Range of names of people Age Integer, age when person died on Mt Everest Range of ages in integer values Expedition Character String, Name of Mt Everest Climbing Expedition Range of Expeditions Nationality Character String, Nationality of Person who died on Mt Everest Range of Nationalities Cause_Death Character String, Cause of Death Range of causes of death Location Location of death on Mt Everest Range of locations on Mt Everest With the MtEverestDeaths.xlsx data set use Tableau Desktop to produce three different views of Deaths that have occurred in expeditions attempting to climb Mt Everest. Note you will find it useful to do some research on the Deaths that have occurred in expeditions attempting to climb Mt Everest in order to comment on each of three views of Deaths on Mt Everest that you will need to create for Task 3.1, 3.2 and 3.3. Task 3.1) Create a view of the Deaths on Mt Everest in a Tableau Text Table or Graph view that displays by Nationality, No_Deaths over time (in years). Comment on the key trends and patterns that are apparent in this Text Table/Graph (about 50 words). Task 3.2) Create a view of the Deaths on Mt Everest in a Tableau Text Table or Graph view that displays by Location, Cause of Death, and Nationality. Comment on the key trends and patterns that are apparent in this Text Table/Graph (about 50 words). Task 3.3) Create a view of the Deaths on Mt Everest in a Text Table or Graph view that displays by Expedition, Cause of Death and Nationality. Comment on the key trends and patterns that are apparent in this Text Table/Graph (about 50 words). Note that you need provide a copy of each Text Table or Graph view in your Assignment 2 report for the relevant sub Tasks 3.1, 3.2 and 3.3. The Tableau Menu / Worksheet and then Copy or Export Options will allow you to copy and paste the view for each Text table or Graph into relevant section of Task 3 for your Assignment 2 report. Note you need to provide a copy of your Assignment 2 Task 3 Tableau file in twbx format as part of your Assignment 2 submissionYour assignment 2 report must be structured in report format as follows: Title Page for Assignment 2 Report Table of Contents Body of report – main sections and subsections for assignment 2 tasks and sub tasks so Task 1 will be a main heading with appropriate sub headings etc....for each sub task such as Task 1.1, Task 1.2 etc.. Task 2 … Task 3 …. List of References List of Appendices You need to submit two files for Assignment 2: 1. Assignment 2 Report for Tasks 1, 2 and 3 in Word document format with the extension .docx 2. Tableau packaged workbook with the extension .twbx contains three required Text Table / Graph views for Task 3 Use the following file naming convention: 1. Student_no_Student_name_CIS8008_Ass2.docx and 2. Student_no_Student_name_CIS8008_Ass2.twbx Harvard referencing resources Install a bibliography referencing tool – Endnote which integrates with your word processor. http://www.usq.edu.au/library/referencing/endnote-bibliographic-software. USQ Library how to reference correctly using the Harvard referencing system https://www.usq.edu.au/library/referencing/harvard-agps-referencing-guide