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ISY5007 Assignment

by | May 22

ISY5007 Assignment – Report on Data Management Plan (S1/2020)
30% of the final assessmentIndividual Assessment1500 words maximum, excluding appendix
Write a data management plan for ONE of the data science project scenarios given below OR seek approval in writing from the Unit Coordinator for an alternate scenario of your choice.
Your data management plan should identify data sources and articulate a reasonable approach to data acquisition, cleaning, integration, archival and analysis.
Consideration should be given to hardware/software and processing requirements.
Consider using measured, estimated, or simulated data to demonstrate the kind of data that you anticipate this project will use.
From a high-level perspective describe in English how you anticipate this data will be analysed. You may consider using pseudo code to illustrate this or use Python or a similar programming language if you have the necessary skills. Note that actually analysing data is not a requirement for this assessment.
The goal of this assessment is to demonstrate

expectations related to data volume, velocity, and variety, veracity, and value
planning for metadata content and format
a reasonable approach to project governance
recommendations for data storage, publication, archival, and retirement
strategies to guarantee data quality, security, and privacy

Scenario Choices
Scenario 1: Your organisation aims to use data to assist the WA health department in reducing infections from the COVID-19 virus.
Scenario 2: Your organisation aims to use data for targeted advertising that promotes Western Australia as a travel destination.
Scenario 3: Your organisation aims to use data to predict which students are at risk of being terminated or dropping out of their university course.
Scenario 4: Your organisation aims to use data to predict the winner of the American presidential election.
Scenario 5: Your organisation aims to use data to predict the winner of next year’s Brownlow Medal.
Scenario 6: Your organisation aims to use data to predict the likelihood that a start-up company seeking venture capital will become a profitable business.
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