Reference no: EM133705086

Business Intelligence using Big Data

Assessment: Practical and Written Assessment

Assessment Task:

In this assessment, you are required to produce a report based on the Big Data strategy document you developed for Assessment-2(Presentation). You also need to analyse the datasets the business that you identified in Assessment 1 using any big data tools and describe how the outputs of these tools could help you to create the Big Data Strategy. You can include any additional datasets that would support your big data strategy.

At the beginning of the report, you will identify some Big Data use cases based on the Big Data strategies you developed for Assessment 2. In the following part, you will critically analyse different Big Data technologies, data models, processing architectures and query languages and discuss the strengths and limitations of each of them.

You will also discuss different Big Data analytics and business intelligence tools that can be applied on the chosen datasets so businesses can gain actionable insights from Big Data.

Moreover, you will discuss the Big Data technologies that you could use for data collection, storage, transformation, processing and analysis to support your use cases.

You will also illustrate the Big Data technology stack and processing architecture required to support your use cases. You need to provide the rationale behind each of the choices you make. Finally, you will specify what user experiences you are going to provide to aid in decision- making. Your target audience is executive business people who have extensive business experience but limited ICT knowledge. Hence, they would like to be informed as to how new Big Data technologies that you have applied on the datasets could benefit their business. Please note that a standard report structure, including an executive summary, must be adhered to.

The main body of the report should include but not limited to the following topics:

Big Data Use Cases

Critical Analysis of Big Data Technologies

Big Data Architecture Solution

The length of the report should be around 3000 words. You are required to do an extensive reading of more than 10 articles relevant to the chosen Big Data use cases, technologies, architectures and data models. You will need to provide in-text referencing of the chosen articles. Your assessment must have a Cover page (Student name, Student Id, Unit Id, Campus, Lecturer and Tutor name) and Table of Contents (this should be MS word generated).

Assessment Criteria:

You will be assessed based on your ability to critically analyse, use and evaluate different Big Data technologies and to apply Big Data architecture, tools, and technologies to support Big Data use cases. The marking criteria for this assessment are as follows.

Executive Summary

Table of Contents

Introduction
Big Data Use Cases

Critical Analysis of Big Data Technologies - 8 marks Use of Big Data tools on the dataset - 5 marks Critical analysis on the output - 8 marks
Big Data Architecture Solution

Conclusion

References

You are advised to clearly disclose when GenAI tools are utilised in your assessments and are advised to validate the accuracy and reliability of GenAI-generated outputs through rigorous testing and validation processes before incorporating them into assessment, else you will be penalised as per the Academic Integrity Policy and Procedure of CQUniversity. You are also expected to mention the validation processes you have conducted so that the reliability and accuracy of your findings can be confirmed and upheld for the marking as a separate section in the report called "Use and Validation of GenAI Tool", and by completing the survey.

In your report an appendix should be attached answering the following questions. These questions are just to gain the unit and assessment understanding.
Have you used any Generative AI tool to craft your assignment? If Yes, please declare which one.
What specific tasks or aspects of your assignment did you use Generative AI tools for?
Did you find Generative AI tools helpful in enhancing your productivity or creativity during the assignment process? If so, how?
Were there any challenges or limitations you encountered when using Generative AI tools for your assignment?
How did the use of Generative AI tools influence the quality or outcome of your assignment?
Did you collaborate with others while using Generative AI tools for your assignment? If yes, how did this collaboration influence your use of Generative AI tools and the overall assignment process?
Did you receive any guidance or training on how to use Generative AI tools effectively for academic assignments?