Principles and Methods of Data Analysis COM427
Why is this module important?
In order become a proficient Data Analyst and work effectively with data, you will need to understand a wide range of concepts and principles about data, to recognise the different types of data, its lifecycle, the dimensions of data quality, architecture and the legislation affecting its use. As a Data Analyst, you will be required to solve specific problems using data, to interpret, confirm and work to a set of customer requirements provided to you, to use a range of methods and techniques to analyse the data and present it in a way that is appropriate to the audience and this module will introduce some practical methods and tools to achieve these tasks.
What will you learn on the module?
The purpose of this module is to provide you with a fundamental understanding of core principles of data including understanding the different types of data, data quality, lifecycle and architecture along with an overview of the main legislation, security and ethics when collecting, storing and processing data.You will also look at the information requirements of organisations and explore how to model, analyse and present the data to meet those requirements. In doing so, you will use basic numerical and statistical techniques, languages and tools.
By the end of this module you will be able to:
- Understand the different types of data, including open, public and proprietary data, administrative and research data, structured, semi-structured and unstructured data.
- Describe the principles of the data life cycle and the steps and different methods involved in carrying out routine data analysis tasks.
- Understand and apply statistical methods to data analysis tasks.
- Interpret customer requirements, analysing and presenting data to meet those requirements, be able to successfully interpret and identify trends and patterns in data sets and present the results and findings from your data analysis in a way that is clear, informative and appropriate to the audience.
- Awareness of the current relevant legislation and its application to the safe use of data. Understand the ethical aspects associated with the collection, storage, and usage of data.
- Identify the different data quality dimensions and understand the risks inherent in poor quality data and how to mitigate or resolve these.
Assessments
The module has two summative assessments each of which will require you to interpret a set of customer requirements and a sample data set, to apply the methods, techniques, and tools you have learned to complete some data analysis tasks and present your results and findings. For the first summative assessment, you will also be required to look at the data quality issues and recommend ways in which these can be addressed.Data Analysis and Data Quality 2000 word Report
AE1 - Report 2000 words (40%) For the first summative assessment, you will also be required to look at the data quality issues and recommend ways in which these can be addressed.
AE2 - Oral assessment and presentation 10 Mins (60%) For the second summative assessment, you will be required you to deliver a short presentation of your findings and take questions from your tutor.