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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 decision- making (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)

Price: £109

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