Reference no: EM132794759
ICT 370 Data Analytics - King's Own Institute
Learning Outcome 1: Explain the business demand for data collection, decision support and data analytics
Learning Outcome 2: Analyse and evaluate data using different data analytics layers and techniques
Learning Outcome 3: Justify choices for data design in big data context
Learning Outcome 4: Select and apply data modelling tools to business intelligence scenarios.
Assessment
Group project - Presentation and Report
Purpose: The purpose of this assessment is that students will learn different Analytics techniques by searching for data sets and then analyzing these data sets using different tools and also by listening to presentations made by their peers. This assessment contributes to learning outcomes a, b, d.
Assessment topic: Students to select a data source and suggest a topic of analysis for that data source. Tutors to approve the topic before students proceed further.
Task details: Students will work in groups (minimum 3 and maximum 4 students in each group) on data set identified by them and approved by their tutor.
They will apply analytical methods to select a data set and summarize some of target models in Descriptive and Predictive Analytic layers to get it approved for their project. They will then use any analytical tools (e.g. Excel, Tableau, Rapid Miner) to extract their findings and draw insights from this data set.
The outcomes need to presented using Visualization models and also explained in a detailed report as explained below.
Students will present their findings as a group during tutorial sessions in week 10 for a duration of 10-15 mins per group. Tutors will provide feedback on their findings and students will then need to update their findings to reflect this feedback in their group report.
Submission of group report will be due in Week 11. This will be 2,000 words report excluding references and executive summary. It should consist of the following structure:
• Title Page (Student's name and ID, Tutor's name)
• Executive Summary
• Table of contents
• Introduction (usually includes below section to explain the Data Set and its background):
o Brief background information
o Purpose
o Scope
o Definition of terms
• Data Analysis Findings (could consist of):
o Review of literature related to similar data sets
o Summary of Groups Findings
o Discussion about findings including any models and Visualizations to support the findings
• Conclusion/recommendations (Response to Feedback and also any other suggestions to provide improvements in data set or findings)
Attachment:- Data Analytics.rar
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