COM618 The amount of data in the world is exploding. In particular, the healthcare industry is generating large amounts of data: Data Science Report, UOC, UK

Task

The amount of data in the world is exploding. In particular, the healthcare industry is generating large amounts of data, driven by a wide range of medical and healthcare functions, including clinical records, medical images, genomic data, health behaviors, clinical decision support, disease surveillance, and public health management. The challenges include capturing, storing, searching, sharing, analyzing, and then finding insights from complex, noisy, heterogeneous, longitudinal, and voluminous data. 

To take advantage of the massive amounts of data in healthcare fields and provide the right intervention to patients, methods such as personalized care, visualization tools, and predictive models can help benefit all the end users of a healthcare system. Big data analytics needs to bridge data mining and healthcare informatics communities.

Part A 

You need to search for open datasets, import some medical data, and manipulate the data by using appropriate visualization tools or libraries of your choice. The visualization of the chosen dataset must be documented by providing a rationale behind using either of the tools and its relevance in the healthcare sector. 
Some sources of open datasets that can be explored:

• Google Dataset search
• Data.gov.uk
• WHO
• Dataverse
• Office for National Statistics 

You can also use other relevant sources to gather your health dataset. Your report should justify your choice of datasets and be informed by research.

Data Preparation: Assess the quality of your data using suitable techniques. Clean the data if and as necessary. Your report should document and justify any techniques you have utilized to assess the quality of the data. Your justification must be informed by research.
Data Exploration: Utilise suitable data mining tools and analysis techniques to find significant patterns and trends (SPSS, Excel, Tableau, WEKA, Python libraries, etc). Explain the patterns you have observed.

Part B

Your report should present a proposal on how you identified a problem in the dataset and how you can construct a model to make predictions or forecast trends. 
Data Modelling and Visualisation: Use appropriate tools to perform some visualization on the chosen dataset. The choice is yours, based on your future intention of work and also your familiarity with the tool. Your report should document and justify the techniques you have used to mine and analyze the data and the patterns or trends that were discovered. Finally, construct a model that can make some predictions or forecast trends.
Evaluation: Critically evaluate your results and compare your findings to other similar studies.

For both part A and B, it is important to provide evidence (related work) from the literature and case study examples for your chosen tool in the healthcare data analysis domain.