Reference no: EM132587664

Programming for Big Data - Higher Diploma in Data Analytics

Project Description

You are required to carry out a series of analyses on publicly accessible datasets using the R programming language used in this module and programming environments suitable for the task. It is recommended that your use at least two separate datasets. For each of the chosen datasets you are required to compile a report of your analysis. Each dataset should have at least 1,000 records (rows). If you are unsure if your dataset(s) is/are appropriate, please check with your lecturer. You must provide evidence in your report that you are authorized to use the dataset(s) that you have chosen.

The main deliverable is a report that provides significant insights into the datasets that you have chosen to analyse. Your report should provide at least four unique insights based on your data analysis. Examples of insights might include relationships, trends/patterns, correlations, models based on the data, visuals, and statistical analyses.

All deliverables should be compiled into a project report document for submission including all programming code elements in an appendix. Please submit your report via the Turnitin upload link in Moodle. R scripts and additional files are to be uploaded to a separate link in Moodle. Your project report should discuss the challenges that you encountered while handling your chosen datasets and the means and mechanisms you implemented to overcome these challenges. The word count for your report should be not less than 2,000 words, and not more than 2,500 words (not counting R code).

Structure and Rating Grid

• Description of the objective(s) of the analysis with reference to basic domain literature to explain the domain purpose of the analyses

• Description of the underlying dataset including an assessment of the data types present, with an emphasis on the data that is actually used in the analytical processes

• Approach to the analysis, aided by visuals such as diagrams, flowcharts, tables, and pseudocode, where appropriate

• R code demonstrating at least four unique insights. R scripts will be executed as part of the assessment process. It is expected that scripts are fully working, efficient, commented clearly, and do not contain excess code

• Project report structure, presentation and discussion of challenges.

Attachment:- Diploma in Data Analytics.rar