Assignment Task: As part of the formal assessment for the programme you are required to submit a Data Handling and Decision Making report. Please refer to your Student Handbook for full details of the programme assessment scheme and general information on preparing and submitting assignments.
Learning Outcomes:
After completing the module, you should be able to:
A) Analyse methods of auditing data holdings and gap identification.
B) Critically analyse theoretical and core processes of data manipulation and mining.
C) Utilise and evaluate basic statistical concepts.
D) Appreciate ethical issues and their importance to data handling and decision making.
E) Develop a practical ability with data analysis and data mining methods to analyse and interpret data sets.
F) Make recommendations based upon the findings from data analysis.
G) Graduate Attribute - Effective Communication
Communicate effectively both, verbally and in writing, using a range of media widely used in relevant professional context.
Maximum word count: 5,000 words
This assignment is worth 100% of the marks for this module.
The aim of this assignment is twofold:
1) Conduct and report on an audit of the data environment in an organisation of your choice.
2) Based on the outcomes of the audit, develop a report presenting statistical analysis of a large data set coupled with a concluding narrative demonstrating appropriate recommendations.
An audit of the data environment an organisation operates in represents a starting point in developing a big data analytics framework, and as such, is a key part of data enabled decision-making at all levels.
This audit should include the following processes:
a) Identification of major data sources and flows between the organisation and its stakeholders;
b) Formulation of the improvement in data integrity as well as its storing, processing and reporting mechanisms;
c) Recommendations on compliance procedures, specifically, data protection, privacy and ethical assurance.
A statistical analysis of a large data set is used to support and enhance the decision-making process in a case organisation. It should include the following components.
- Identification of a strategic decision which can be supported by data analytics;
- Description of relevant dataset;
- Selection and application of data mining procedures to the data set in question.
- Development of a report on forecasting and/or trends obtained through data mining, which should be visualised with tables, charts and diagrams.
- Recommendations based on the outcomes of the aforementioned analysis.
Question 1: What are the key sources and flows of data that are collected, processed, stored and taken into account in the organisation's decision-making process? Your response must include:
i) A statement of all the current financial and non-financial data the organisation uses in its decision making;
ii) An analysis of data integrity and identified gaps;
iii) A map between business functions and data sources.
Question 2: Based on the outcomes of your response to Question 1, a specific proposal must be developed on a streamlined and more informed decision making based on (a) additional analysis of the currently observed data, and (b) any extra types of data that can be retrieved, stored and processed for augmenting the currently available information. Your response must include:
i) Description of data flows between the organisation and all of its stakeholders identified and ranked in terms of their relevance to strategic, tactical, and operational decision making;
ii) An approach to the improvement in data integrity of the proposed data analytics framework;
iii) Data protection and ethical assurance requirements.
Question 3: Statement of a specific decision the organisation currently needs to make, and how big data are expected to improve its quality. Your response must include:
i) A statement of major strategic decisions and how the current financial and non- financial data are currently used in respective decision making;
ii) Statement of a particular decision selected for data analysis, and its critical importance for the organisational competitive advantage or performance improvement;
iii) Identification of a specific data set to be analysed for supporting the stated decision. The assignment must utilise a large data set obtained from the chosen organisation.
Question 4: Description of a relevant dataset to be applied for the improvement of the selected decision, including:
i) Discussion of business-related information the dataset represents;
ii) Explanation how it has been obtained;
iii) Analysis of how representative the data set is, and potential limitations associated with its application.
Question 5: Discussion of data mining procedures with the dataset in question, performed using Excel, SPSS and / or Weka, which include:
i) Data preparation, cleaning and filtering;
ii) Statement of immediate observations of business performance using descriptive data analysis;
iii) Development of an organisation's forecast report based on inferential data analysis and / or application of machine learning techniques.
Question 6: Visualisation and interpretation of results as expected in business and academic reporting - this discussion must be supported extensively by tables, charts and diagrams demonstrating how the outcomes of analysis performed in the previous task can be interpreted.
Question 7: Recommendations for the decision making based on the analysis described earlier as well as a proposal on the deployment of extra data sources potentially capable of further augmenting the organisational big data framework.
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