Teaching Responsibility

LJMU Schools involved in Delivery:

Computer Science and Mathematics

Learning Methods

Lecture

Practical

Module Offerings

5124COMP-SEP-CTY

Aims

To contextualize the place of data science and the data analysis process in the organization To introduce the hierarchy and uses of different analytical approaches

Learning Outcomes

1.
Distinguish between the component parts of enterprise information management systems and the place and purpose of data analytics and data science within those systems.
2.
Identify and differentiate the component parts of the data analysis process.
3.
Differentiate between the types of analytic approaches available and what each can produce

Module Content

Outline Syllabus:Enterprise information management systems Enterprise Information Management (EIM) Enterprise Data Analytics (EDA) Enterprise Data Science (EDS) Enterprise Architecture (EA) Enterprise solutions (ES) Data Analysis Process Data Analytics Types Descriptive Analytics – summarize “historical” data Decision Analytics – distil data into manageable sets to optimise decision-making Predictive Analytics – forecast future outcomes Prescriptive Analytics – identify possible future actions and their effects Detailed examples of descriptive and decision analytics in practice The data science process Raw data collection Data cleansing Exploratory data analysis Machine learning, algorithms, statistical models Communicate, Visualization, Report findings Build data product Cases studies in data analytics/science
Module Overview:
To contextualize the place of data science and the data analysis process in the organization To introduce the hierarchy and uses of different analytical approaches This module contextualises the roles of data science and data analytics in organisations to demonstrate their differing contributions to those organisations. In doing so, a hierarchy differing type of analytics are introduced and differentiated from data science in terms of purpose. This module lays the groundwork for the development of these areas in future modules, although descriptive and decision analytics are covered in detail here.
Additional Information:This module contextualises the roles of data science and data analytics in organisations to demonstrate their differing contributions to those organisations. In doing so, a hierarchy differing type of analytics are introduced and differentiated from data science in terms of purpose. This module lays the groundwork for the development of these areas in future modules, although descriptive and decision analytics are covered in detail here.

Assessments

Report

Centralised Exam