Real-Time Data Analytics Adoption Strategy and Implementation

Significance of Aspects in Real-Time Data Analytics Adoption Strategy

On successful completion of this module students will be able to

1.A critical understanding of the knowledge base in Data Science and its inter-relationship with other modules in the programme such as Big Data and Analytics.

2.An ability to work with ideas developed in Data Science at a level of abstraction, arguing from competing perspectives, and identifying the possibility of new concepts within existing knowledge frameworks and relevant approaches.

3.An ability with and confidence in identifying and defining complex problems, and selecting and using investigative strategies and techniques to undertake a critical analysis of machine learning models, and evaluating the outcomes of this analysis.

To analyse new, novel and/or abstract data using an appropriate range of established techniques relevant to machine learning algorithms; as well as judging the reliability, validity and significance of evidence to support conclusions and/or recommendations relevant to the subject covered by this module.

In assignment 1 of this module, you have developed a ‘data analytics engine’ using machine learning and data analytics approaches.

After reviewing the benefits of the ‘data analytics engine’, you are asked to implement your analytics engine for performing a real-time data analysis processing implementation.

The aim of this assignment is to critically evaluate and reflect on the developing of an ‘enterprise wide real-time data analytics adoption’ strategy. This report is divided into the following tasks:

Task-1: Critically evaluate the significance of the following aspects in your real-time data analytics adoption strategy:

·Data Ingestion and aggregation

·Role of Data Mart and Data Warehouse

·Advantages/disadvantages of real-time data analysis

·Automated analysis using machine learning algorithms

You are also required to provide examples for the above in your critical evaluation. The suggested word limit for this task is 600 words.

Task-2: Compare and contrast the following data processing options/aspects for your enterprise wide data analytics strategy:

·Complex event processing

·Extract, Transform & Load (ETL) Pipeline

·Interactive dashboards

·Geo-spatial analysis

Task-3: Data stream processing plays a pivotal role in a real-time data analytics adoption strategy. In this task, provide recommendations for developing an automated data stream processing pipeline for performing Business Intelligence (BI) in the organisation of the Assignment 1 scenario.

The suggested word limit for this task is 300 words.

Presentation, Report Layout and References:]

Task-1: This task focuses on providing a reflection of your understanding of the important considerations while planning a real-time data analytics adoption strategy. You are required to critically discuss the listed aspects and their significance in the planning phase. It is important to note that you are developing a data analytics adoption strategy for the real-time data

Data Ingestion and Aggregation

Task-2: This task focuses on the operational aspect of a data analytics strategy. You should critically evaluate the listed data processing options as outlined in the task. Your evaluation must include advantages, disadvantages of the technologies involved and limitations of each option. Consider including a comparative table of the listed options for selecting one over the other

Task-3: Data stream processing plays a pivotal role in a real-time data analytics adoption strategy. In this task, you are required to provide recommendations for developing an automated data stream processing pipeline for performing Business Intelligence (BI) in the user organisation for the given scenario. Your answer shall focus on outlining the steps involved for developing a data stream processing.

Presentation, Report Layout and References Your report is well laid out and formatted according to the given requirements. Your report is free from grammatical and spelling errors. Harvard references style has been used to cite the work where necessary and a list of references is also provided. 10

·All components of the assignment (text, diagrams. code etc.) must be submitted in ….one-word file (hand-written text or hand drawn diagrams are not acceptable), any other accompanied materials such as simulation file, code, etc. should be attached in appendices. 

·Standard and commonly used fonts such as Arial or Calibri should be used, font size must be within the range of 10 to 15 points including the headings, body text and any texts within diagrams, 

·Spacing should not be less than 1.5 

·Pay attention to the Assessment criteria / Marking scheme, the work is to be concise and technical. Try to analyse, compare and evaluate rather than simply describe.  

·All figures, screenshots, graphs and tables must be numbered and labelled. 

·Material from external sources must be properly referenced and cited within the text using the Harvard referencing system,  

·The assignment should be logically structured, the core of the report may start by defining the problem / requirements, followed by the proposed solution including a detailed discussion, analysis and evaluation, leading to implementation and testing stage, finally a conclusion and/or personal reflection on learning. 

·Screenshots without description / discussion does not constitute understanding and maybe assumed irrelevant. 

·Please access your Turnitin Test Page via Dashboard or My modules to learn more about Turnitin and to make a test submission and to check your similarity score before uploading your final version  

·You will have opportunity to submit as many times to your module pages as you want up until the deadline. 

·Make sure to make backup of your work to avoid distress for loss or damage of your original work, use multiple storage media (memory stick, cloud and personal computer). 

·Students will have access to formative feedback on each task set in workshops, thereby helping them to refine their approach to the summative tasks that have been set.