Modern Database Models and Technology - IT Assignment Help

Assignment Task

Module Learning Outcomes
Create a data set using modern database models and technology
Manipulate a data set to extract statistics and features,
Critically evaluate and apply data mining techniques/tools to build a classifier or regression model, and predict values for new examples
Analyse and communicate issues with scaling up to large data sets, and use appropriate techniques to scale up the computation,
Critically discuss the need for privacy, identify privacy risks in releasing information, and design techniques to mediate these risks.
This assessment will contribute to all the learning outcomes for this module.
Data
You will find a dataset called brfss_for_bda_2021.csv which describes a survey around health and associated behavioural factors carried out on a population in the US. It’s in CSV format.
Assessment Task(s)
Your task Is to use that dataset, any information you can find about it elsewhere, and the techniques taught in the module, to pose and answer three research questions of your choosing. You will then need to consider how you might store the (research-question-relevant) data in a database, how you might spread a very large version of that data over multiple computers, and what the privacy concerns are here and how you might address them.
Produce a structured analysis report using the given template. The structured report consists of seven sections, each containing specific questions, which you must answer.
In sections 3 and 4 of the report, which require you to use data analysis tools, you may use WEKA or Python tools. In section 3 you may also use Excel for visualisation.
Deliverables
General submission criteria
The submission is a report and final data files. The report must be provided in a format which Canvas can display (i.e. PDF or MS-Word native format), and data files containing the final version of the data that you used for analysis (ARFF or CSV format).
You are expected to research your answers and to cite appropriate academic and/or other sources in an appropriate format (IEEE) for the type of report you have been asked to write. It is probably not sufficient to use only the module notes.
Each part has an indicated maximum word count for your answer. Any cover page and reference lists or bibliographies do not count towards these limits
Exceeding word counts will not be marked.
Your assessment submission should not include your examination number or any other personal identification information.
Assessment Criteria
Question Criteria Available marks
Section 1 – Your data
Uploading data Pass/fail n/a
Section 2 — Business/research questions
Business/research questions The questions are clear (the reader can understand what students are asking), they are plausibly of interest to someone, and they are answerable with the tools studied in the module. 10
Section 3 — Processing the data
Exploring the data There has been useful exploration, given the data and the business/research questions, it has been justified intelligibly, and reasonable conclusions have been drawn. 10
Cleaning/fixing the data Changes to the data are appropriate given the data and business/research questions, and the justification makes that clear. 10

Section 4 — Data analysis
Analysis techniques Analysis techniques are appropriate to the questions, and the justification explains this. 10
Results Results are clear and are plausible (i.e. not obviously invalid). 10
Answers to business/research questions The conclusions are reasonable, traceable clearly to the results, and are indeed answers (or justified observations that there is no clear answer) to the research questions. 10
Residual threats to validity The threats are valid, accurately described, and of genuine concern. 10
Section 5 — Dealing with large data sets
Relational databases Database schema is appropriate (and appropriately normalised). Interface to WEKA is valid and practical. 10
Distributed computation A viable approach using multiple technologies that would likely achieve a worthwhile gain in performance (given coordination overhead etc). 10
Section 6 — Privacy
Privacy issues The privacy issues are of genuine concern and the strategies are plausible solutions to them. 10
 

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