BUSN9165-Big Data Analytics and Visualisation – IT Computer Science Assignment Help

Assignment Task

Task 

Criteria
1. Introductionto data and research question 
Please introduce the data set used and its background. The relevantliterature (e.g., academic journal articles and textbooks) should be surveyed and properly cited with Harvard referencing style.More importantly, please identify a problem to be addressed with this data set(i.e., the research question). Please note that the problem should bespecific(i.e., relevantin theapplication domain and linked to the variables available fromt he dataset.

2.Data processing and exploration
Please explain: Which variables are available from the data set? Which variables have been selected for the analysis and why? Any data transformations have been doneand why?

3.Data visualisation and interpretation 
Please provide at least three data visualisations as descriptive analytical results (e.g., properties of the variables selected) and advanced analytical results (e.g., relationships between the variables selected, machine learning results). Please follow best practices taught in the module regarding data visualization. Importantly, please interpret the results andfindings with details. Note that the data visualisations should be nontrivial representations of information, yet easy to interpret.

4.Data insights and conclusions
Please provide the insights drawn from the analytics and summarise the findings.In particular, is the problem (i.e.,research question)identified at the beginning addressed by the analytics ? How?

5.Writing,styling and references
The clarity, logic and presentation of the report, including spelling,grammar and punctuation. The general styling and references should beclear andconsistent.

2. Recommended data sets
NOTICE: Before starting the individual project, you will need to confirm your choice of dataset with this link on Moodle. 
Please find a list of recommended data sets below. All of them have significant textual content (a major type of unstructured data). Therefore, text analytics tools should be employed. Your analysis could build on existing code shared by the online community (e.g.,from Kaggle.com). If so, please cite the original sources (links or relevant publications) properly in the Harvard referencing style. 

• [Business] Amazon review Office Products [reviews] [product meta data]

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