Reference no: EM133925630

Big Data

Assessment 1: Case Study Analysis Report

Objectives

This assessment item relates to the unit learning outcomes as in the unit descriptor. This assessment is designed to improve student research and writing skills and to give students experience in researching literature on a specific topic relevant to the Unit of Study subject matter. Students will be expected to complete a literature review to discuss contemporary Big Data, access, design or Information design issue which an IS professional may experience. Students will critically analyze current academic papers then present their work in a detailed literature review and analysis.

Assignment Description

This assessment will be completed individually. All students must have a different topic. Students can choose to write about the same technology, but the approach and the thrust of each paper must be different. To ensure the uniqueness and focus of each paper, you must select a specific Big Data topic and title and email it to your tutor for approval within the first two weeks of the unit. Your tutor will either approve your topic or provide feedback requiring you to modify your topic or the approach of your paper.

The narrative should flow logically from one paragraph to the next, avoiding the use of bullet points or small, disjointed sections. Your research should primarily focus on academic papers and other scholarly sources published within the last two to three years to ensure the content is contemporary.

Your paper must be structured with the following mandatory sections:
Introduction
Literature Review
Methodology & Discussion
Result Analysis
Conclusion
Citation and Referencing

You are required to include a minimum of 10 academic references in your paper. It is essential that all references listed at the end of the paper are properly cited within the body of the text and are appropriate to the context of the citation.

Assessment 2: Report -Assessment of high-volume data processing

Assignment Description

Tableau & Splunk Project
The Assignment consists of a research report of 2000 words Due Week 8. The assignment relies on the dataset found in the Assignment2_datasets.zip, which can be downloaded from LMS.

Part 1: Business Data Analysis Problems to be addressed in the report
The report should provide an analysis and evaluation of Global Superstore financial performance over a five-year period from 2014 to 2018 on its global reach of 165 countries. Conduct a comprehensive analysis of revenue, profit, discounts and customer behaviour. Analyse the Key Performance Indicators (KPI) in monitoring, assessing and managing a firm's performance in terms of:

Diverse product range generating higher sales revenue and translation into superior profit
The influence discounts and promotions have on sales and customer loyalty.
Predicting sale trends in product sub-categories in different regions

Investigate which categories and products are the most popular and the most profitable. Should the Global Superstore consider streamlining their products offering, investing more heavily in products which are performing well and removing which are not?

Examine the relationship between purchasing patterns and the percentage of discount applied to determine the impact the discounts and promotions have on sales.
Customer service is another key factor that businesses use to differentiate themselves from their competitors. Determine the volume of repeat customers. Assess the level of customer service that they provide and make recommendations on how they can improve their service and customer retention.
Examine which countries and products have highest return rates. Determine if there are any products that the Global Superstore should consider removing from their product range, as well as aiding them in developing strategies to combat or reduce the rate of return in countries with a high frequency of returns. Perform a return analysis across categories and subcategories.
Evaluate the average shipping cost, most popular mode of shipping and shipping latency to establish if there is a connection between these variables and purchases made. Get expert-level assistance in any subject with our assignment help services.
Predicting future revenue streams is an essential component when determining merchandising decisions.
This report should build a predictive model to determine sales revenue from a given product in each region. This should be limited to the top five sub-categories.
The research report must have the format:

Cover sheet (make sure student no are on the coversheet)
Executive Summary
Table of contents
Company Information
Problem Identification
Data Collection
Analysis and Discussion
Recommendations
References

Part 2: Network Data Analysis
In this part of the assessment, you must analyse the log details of the global super store in Australia with Splunk.
Perform a basic search for errors and any type of failures in all data sources. Provide a screenshot of the entire page once completed.
Perform a new search for password and any type of failures on port 22 in all data sources. Provide a screenshot of the entire page once completed.
Do you see trends over time? If so, what were they?
Use the output of your search to refine the results by adding a new field to the search
Take a screenshot of your ‘Activity Jobs Menu' detailing the current job saved with expiration date.
Take a screenshot of your search history. Set a filter to narrow down your search results.
Show where are selected field, interesting fields and all fields located. How do you use fields to perform a search.

How do you add time range when performing search.

Part 2: Splunk Practical Exercises
Tasks (a-h): Complete each as outlined in the brief.
Screenshots Required:
Screenshots of queries, results, Activity Jobs menu, search history, fields panel, and time range selection.
Short explanations (2-3 sentences per task) interpreting the outcome and trends.
Screenshot requirements:
Screenshots must clearly show the full Splunk interface (not cropped too tightly).
Your Student ID and the current date must be visible on every screenshot.
Screenshots should be pasted directly into the report under each task (a-h), followed by your short explanation.
Screenshots without Student ID visible will not be accepted.