apply any of the analytical tools to develop innovative analytics visualization solutions and predictive models with regards to environment, e.g. climate change, energy consumption, carbon footprint, greenhouse gas emission, pollution dashboard, etc. Besides the suggested datasets/sources, you may apply any other real-world dataset to illustrate your approach

Discussion: Diagnosis And Management Of Respiratory, Cardiovascular, And Genetic Disorders
August 1, 2019
What are the benefits and challenges associated with this change, both from a business perspective and a social perspective?
August 1, 2019

ITECH7407- Real Time Analytic
Individual assignment – 2016
Worth – 20%
ANALYTIC REPORT
This is a business analytics project aimed at generating innovative analytics solutions. It will allow students to show innovation and creativity in applying Watson Analytics/SAP Business Object/Predictive Analytics/HANA and designing useful visualization solutions and predictive models for different types of analytics problems.
The topic will be on environmental issues. Your main task is to apply any of the analytical tools to develop innovative analytics visualization solutions and predictive models with regards to environment, e.g. climate change, energy consumption, carbon footprint, greenhouse gas emission, pollution dashboard, etc. Besides the suggested datasets/sources, you may apply any other real-world dataset to illustrate your approach (the different datasets can be combined too). Please find the attached sample reports
Some possible datasets/sources:
http://data.un.org/Explorer.aspx http://data.worldbank.org/topic/environment https://data.oecd.org/ http://geodata.grid.unep.ch/
http://open-data.europa.eu/en/data/publisher/eea https://www.data.gov/ Watson Analytics Tutorials:
http://bigdatauniversity.com/courses/watson-analytics-fundamentals/ Watson Analytics -IBM TV How-To Videos:
https://www.youtube.com/channel/UC6D7Ekh27J6Axp9BNKyLQ3w
Report Submission: Hard-copy to tutors/lecturers assignment box in week 10. Doublesided printing for the hard-copy is encouraged in order to save paper.
You will also submit a 9-10 pages report (about 3000 words not counting cover page and references) of this project. At least 15 references in your report must be from peerreviewed sources. Include any and all sources of information including any person(s) you interviewed for this project.
Please note that all references must adhere to APA style. See http://owl.english.purdue.edu/owl/resource/560/01 and http://www.apastyle.org/ for details on how to format a report and how to cite references. Make sure your follow formal report structure with cover page, introduction, use of headings, subheadings, conclusion sand reference section. You are reminded to read the “Plagiarism” section of the
course description. Your essay should be a synthesis of ideas from a variety of sources expressed in your own words.
All reports must use the APA referencing style.
University Referencing/Citation Style Guide:
The University has published a style guide to help students correctly reference and cite information they use in assignments (American Psychological Association (APA) citation style, http://www.ballarat.edu.au/aasp/student/learning_support/generalguide/print/ch06s04.shtml or Australian citation style
Reports are to be presented in hard copy in size 12 Arial Font and double spaced. Your report should include a list of references used in the essay and a bibliography of the wider reading you have done to familiarize yourself on the topic.
A passing grade will be awarded to assignments adequately addressing all assessment criteria. Higher grades require better quality and more effort. For example, a minimum is set on the wider reading required. A student reading vastly more than this minimum will be better prepared to discuss the issues in depth and consequently their report is likely to be of a higher quality. So before submitting, please read through the assessment criteria very carefully


 

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The post apply any of the analytical tools to develop innovative analytics visualization solutions and predictive models with regards to environment, e.g. climate change, energy consumption, carbon footprint, greenhouse gas emission, pollution dashboard, etc. Besides the suggested datasets/sources, you may apply any other real-world dataset to illustrate your approach appeared first on Homework Handlers.


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