BS185 L7 Data and Decision Making Assessment Brief | ULaw

Learning outcomes:

1. Critical awareness and understanding of data types, their collection and processes involved in the data pipeline.
2. Critical evaluate various forms of databases and their management requirements.
3. Ability to critically evaluate current and future challenges, limitations and opportunities in data management.
4. Practically apply data management solutions to resolve issues.

Assessment details: Individual written report, 100% (2,500 words)

Referencing: 

Students are expected to use Harvard Referencing throughout their assignments where required. Please follow the Harvard Referencing Handbook for all your assignments at the ULBS.

Submission Method: 

Turnitin - Your work will be put through Turnitin. All submissions will be electronically checked for plagiarism and the use of AI software.

You have the option to upload your work ahead of the deadline, more than once. ULBS will be reviewing your last submission only. You can only upload one file. For example if your work contains a word document and power point slides/Excel spreadsheet you will need to copy your slides/spreadsheet into the word document.

BS185 Assignment Details

This assignment comprises of a report that critically explores potential a data-driven decision-making solution in any industry of your choice. You will use solutions and supplementary narrative developed through the semester to aide with critically exploring potential data-driven decision-making in the industry of your choice.

The report activities are as follows [LO 1.2.3.4]:

Identify an industry and topic: Consider an application area for data management that you are particularly interested in (e.g., Finance. healthcare, massive transportation, social networking, smart home, cyber security, business intelligence, or any other application areas where data management have been used/adopted). Then, a more specific topic within the area should be identified and focused on (e.g., the use of data and decision-making for disease diagnose/prediction rather than the broad area of healthcare).

After selecting a problem, you will investigate and discuss the following tasks:

• What business data driven decision will you discuss and analyse?
• Critically evaluate two different sources of data; data types, methods for collecting the data, storage and management, and suggest solutions.
• Critically examine, transform and explore the two data sets using univariate and multivariate techniques taught in workshops. You must use Python and include full screenshots of Colab with the Python code and share the Colab file link in the appendices. Reference the appendix (e.g. (see appendices A)) in the main body. Charts and tables should be in the main body of the report to support your interpretation of the results of your analysis. All charts and tables should reference the source(s) of the data.
• Critically report on the findings from the analysis, a clear recommendation, that includes current and future direction of data management for business, for your business problem, and limitations of your data management solution for the identified business problem.

In the consolidation section of Units 2 to 9 on Elite there are critical discussions on various topics.

You should.

• Add a minimum of five responses across all topics discussed in Units 2 to 9.
• Screenshot a minimum of the five of your responses to the topics, and add them to the appendices of the report and label each appropriately e.g. Appendices B, Appendices C, Appendices D and Appendices E.
• All responses to topics must be within five working days of the associated unit workshop and be evidenced with academic and practice references.
• Critically use and reference (e.g. (see Appendices B)) the responses in your report discussion.

Secondary sources of data: There are several online open sources for data exploration. Some of them are listed below:

• Statista - Access through the library
• Dataset Search (google.com)
• kaggle datasets
• Datasets | fp20 analytics
• Data.gov.uk
• Data.world
• Databank.worldbank.org
• Research datasets | Bank of England
• Yahoo Finance
• Cryptodata

Scrapping Data: You may wish to scrape data from the internet. Reminder: If you want to collect data from sources other than those listed above. Data should be sourced, stored and handled ethically. If you want to scrape data check with your module tutor and complete an appropriate ethics process.

Completed ethics forms must be added to the appendices.

General guidelines

The report should contain:

• Title page
• Executive summary (included in the word count approximately 100 words)
• Contents page
• Introduction (included in the word count approximately 200 words)
• Main section which should include subsections for tasks 1-4 (included in the word count approximately 1,400 words)
• Findings (included in the word count approximately 350 words)
• Recommendations (included in the word count approximately 200 words)
• Limitations (included in the word count approximately 150 words)
• Conclusion (included in the word count approximately 200 words)
• Reference list
• Appendices

Section headings, table or chart headings or footers, table or data, page numbers, references and direct quotes do not count towards the word count.

Please refer to the marking criteria (below) for a breakdown of how the tasks will be marked.

BS185 Assessment Criteria