COMPGC27 - Programming for Business Analytics
This database contains 2016-17 versions of the syllabuses. For current versions please see here.
|Taught By||Daniel Hulme, with guest lecturers (100%)|
Increasingly firms are using the data to develop new insights about their customers and their behaviours. Beyond consumer markets, (big) data-driven decision making is increasingly making its presence felt in the business-to-business and business-to-government sectors. Some organisations are even innovating their whole business models, creating new services through the novel application of data. As data-driven strategies take hold, they will become an increasingly important point of competitive differentiation. This module will provide you with a broad understanding of Data, you will utilise cutting-edge tool that will emphasizes the importance of developing adequate business models providing appropriate incentives for private-sector actors to share and use data for the benefit of the individual, firm and society.
Upon successful completion of the module, a student will be able to:
- Data storage, security, processing, governance
- Data scraping, cleansing and de-duping
- Characteristics of useful Data
- Big Data, Linked Data and the Semantic Web
- Issues surrounding Public and Private Data
- DIKUW Pyramid
- Structured, Unstructured, Semi-structured
- Data Visualisation and Manipulation
- Descriptive, Predictive and Prescriptive data
- Extensive use of Data tools
Method of Instruction
Lectures, seminars and workshops, with heavy emphasis on independent learning.
The course has the following assessment components:
- 1 Group Coursework (50%)
- 1 Individual Coursework (50%)
To pass this course, students must:
- Obtain an overall pass mark of 50%.
- Data Science for Business: What you Need to Know about Data Mining and Data Analytic Thinking, T. Fawcett and F. Provost, O’Reilly, 2013.
- Thinking with Data: How to Turn Information into Insights, M. Shron, O’Reilly, 2014.