Reference no: EM132635100

MITS6005 Big Data - Victorian Institute of Technology

Learning Outcome 1: Expertly apply techniques to perform big data query manipulation, evaluate various data storage option and type of aggregated data modelling. Through a critical study, choose an appropriate storage model based on the application requirements for processing large amounts of structured and unstructured data.

Learning Outcome 2: Independently perform data manipulation and querying (including updates, transactions, and indexes) big data applications dealing with high volume using NoSQL. Organize, store the collected data and manipulate by crafting queries. For example, using Hive, HBase and related data tools.

Learning Outcome 3: Carry out research on emerging Big Data technologies to evolve models/solutions such as configurable and executable compute jobs on top of using distributed and shared memory architecture and Resilient Distributed Data Sets (RDDs).

Learning Outcome 4: Implement typical solution use cases in big data context using technologies such as MapReduce and Spark Framework and using ecosystems such as Hadoop (or other similar platform).

Objective

You will work with your group and leverage the data provided by Pixystems (see the Data Overview above for a high-level explanation of data provided) and information obtained from the CFO to identify areas for financial and operational improvement, address issues and errors found in processing of data. To do this your group must create analytics that will assess the validity of data and provide the insight the CFO is looking for.

It is expecting that you have a visualization report representing the analytical procedures you performed and assumptions you made. The project data required for the given case study is provided in "Fictional Project Data.xlsx" with the relevant records as tabs in the spreadsheets. You will have 10 mins minutes to present this visualization, assumptions made, and recommendations. Each member of your group must have an active speaking role within the presentation.

Description
Read carefully "Pixystems_Toys_Information.pdf" file. You are going to do the analytics using Packages in Python. You can use "Tableau Server Client" and write your code in Python. or you can use other libraries in Python; it is your choice. Python is one of the most frequently used programming languages in many fields, particularly in data science. There are many libraries in Python for various tasks including big data and data visualization. You must do some research on python packages, find proper ones for the below task and use them for analysis and writing your report. But at the end, we expect a quality work from you. For Python code, you can use Python Anaconda or Google Colab. Colab is a free notebook environment that requires no setup and runs entirely in the cloud. You need to login to google Colab to enable to use it.

Your report should have 1000-1500 words addressing the business questions, challenges, analytics and data visualization in "Pixystems_Toys_Information.pdf". It should cover what you are going to solve and how, plots and recommendations. The report should have at least 6-10 plots (screenshots) from your findings with explanations. The python code needs to be added at the end of the project. The template of the word file is provided as "MITS6005-Report format for assignment-3.doc".
The presentation should be a maximum of 10 minutes for the whole team. Each member should talk at least 2 minutes related to the project and findings. The whole presentation should cover the data, business questions, research findings and visualization and step by step discussion on how you've achieved this project.

You will also prepare a final report outlining the following:

• Results of the analytics you performed along with your rational for performing and assumptions made.
• Insight that the analytics provided management
• Explanation of any analytics you decided not to perform
• Recommendations your team has for improving Pixystems' processes
• Overview of any other issues that Pixystems should follow-up on
• Recommendations on system controls that could be put in place
• Any other data you would like to have obtained from Pixystems

General Instructions

1. Your writing should be clear and concise and be in your own words.
2. The report must be in the range of 1,500-2,500 words in length excluding references.
3. Your report should be a single word or pdf document containing your report and need to be submitted through Moodle.
4. One submission per group and make sure all group members there with contribution table at the end of the report.
5. One submission per group and make sure all group members are active in the video with at least 2 minutes talk from the project.
6. Use headings to guide the reader and include tables or diagrams that make the case clearer.
7. The python code needs to be attached at the end of the report as an Appendix.
8. The referencing style must follow the IEEE referencing style.

Pixystems Toys Project

Assignment Details:

You will work with your team and leverage the data provided by Pixystems (see the Data Overview above for a high-level explanation of data provided) and information obtained from the CFO to identify areas for financial and operational improvement, address issues and errors found in processing or data, and confirm the information that the CFO shared with your team. To do this your group must create analytics that will assess the validity of data and provide the insight the CFO is looking for.

You will meet again with the CFO on 25 Oct 2020 to deliver your results. She is expecting that you have a Tableau visualization representing the analytical procedures you performed and assumptions you made. You will have 10 mins minutes to present this visualization, assumptions made, and recommendations. Each member of your group must have an active speaking role within the presentation.

You will also prepare a final report outlining the following:
• Results of the analytics you performed along with your rational for performing and assumptions made
• Insight that the analytics provided management
• Explanation of any analytics you decided not to perform
• Recommendations your team has for improving Pixystems' processes
• Overview of any other issues that Pixystems should follow-up on
• Recommendations on system controls that could be put in place
• Any other data you would like to have obtained from Pixystems

You will be assessed as follows:

1. Structure of the written report
2. Choice of the analytics: Method chosen and Rationale for performing analysis.
3. Results of the analytics: Output of Analytics and Discussion of it in context of case study.
4. Write clearly and concisely: Arguments are explicit and succinct, appropriate headings are used, grammar and spelling are accurate.
5. Presentation: Presentation Style, Content and Q&A

Attachment:- Big Data.rar