Cloud Computing Programming for Data Analytics - Engineering Assignment Help

Assignment Task :

1 Objectives
You are required to identify and carry out a series of analyses (i.e., at least two) of a large dataset or a collection of large datasets utilising appropriate programming languages and programming environments.
Your project must incorporate the following elements:
1. Utilisation of MapReduce-style processing environment for some part of the analysis.
2. Source dataset(s) should be stored in appropriate database(s) prior to processing
3. Post-MapReduce processing dataset(s) should be stored in appropriate database(s)
4. The source data must be programmatically accessed by the code that processes it
5. The output of the MapReduce processes must be programmatically stored
6. Follow-up analysis must be carried out the MapReduce output data
For example, you may initially utilise HBase, MongoDB, Cassandra, Riak or some other NoSQL database to store the raw datasets, then the processing would utilise this database as an input source. Note that the choice of database used as the input source should be informed by the format of the data and the nature of the processing operations you wish to carry out. Once the data have been processed, they could be stored in MySQL or PostgreSQL databases.
Following that you may use Python with NumPy/Pandas with Matplotlib or R with ggplot/plotly to conduct further analysis of the output data (e.g., statistical analysis and/or data visualisation.
 

2 Deliverables

The results of the analysis must be presented in the form of project report. This report should discuss the program- ming and data handling challenges that you encountered and the techniques you used to overcome these challenges.

The report should be 3000 ± 300 words in length (excluding references), and must follow the IEEE format1 in addition to be employing appropriate referencing methods (again IEEE standard) and a suitable academic writing
style. The report should include the following:
1. A description of the source dataset(s), including data types, ranges, cardinality and number of missing values;
2. A description of the objective of the analysis. Note that the analysis should attempt to answer a novel question and should be backed up by references to suitable literature;
3. Details of the data processing activities carried out, including preparation of the data and processing the data in a MapReduce-type environment. This should include all MapReduce patterns employed.
4. A discussion of the rationale and justification for the choices you have made in terms of data processing, programming language choice, and algorithms that you have implemented; and
5. Presentation of results by making appropriate use of figures, tables, etc., with an accompanying textual evaluation.

This Engineering Assignment has been solved by our Engineering  Experts at My Uni Paper. Our Assignment Writing Experts are efficient to provide a fresh solution to this question. We are serving more than 10000+ Students in Australia, UK & US by helping them to score HD in their academics. Our Experts are well trained to follow all marking rubrics & referencing style.

Be it a used or new solution, the quality of the work submitted by our assignment experts remains unhampered. You may continue to expect the same or even better quality with the used and new assignment solution files respectively. There’s one thing to be noticed that you could choose one between the two and acquire an HD either way. You could choose a new assignment solution file to get yourself an exclusive, plagiarism (with free Turnitin file), expert quality assignment or order an old solution file that was considered worthy of the highest distinction.