Data Discovery Visualisation Individual Report, 3500 words -- 2

Data Discovery Visualisation

Individual Report, 3500 words

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Free of plagiarism

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Report DETAILS

Develop a Digital Data Analytics prototype project with an associated business

planning document.

choose organisation as a context.

Use a method to help guide and justify your proposal.

you should include the following:

1- A Business Plan detailing the strategic context of the client organisation, and

the specific potential contribution of the prototype has in achieving the strategic

goals;

2-A summary of a Project Plan which details the proposed benefits, risk, skills and

resource considerations, outline work breakdown structures;

3-A prototype of the technologies being proposed. This should include the

following:

4- A proposed prototype or conceptual model that uses the key technologies

of Digital Data Analytics, e.g. data server technology (e.g. on

AWS/GCP/Azure or another cloud based server), linked to a data analysis

technology (e.g. Tableau, Qlik).

5- A justification of the selected technologies;

6-A discussion on the methodological, professional and ethical issues associated

with your prototype specifically, and with Data Analytics Technologies in a more

general sense;

7- A reflective assessment of the limits of your own personal knowledge and skills

to undertake the role of leading a Digital Analytics project.

Issues of scope and inquiry

8-You may want to identify a small and focused application of Digital Analytics in

your department or business unit. Or, you may want to develop the scope more

widely. e.g. in a sector, supply chain etc.

A thorough piece will be able to identify ‘what you do not know’ as well as ‘what you

do know’. For example, a given proposed idea on the application of Digital Analytics

technologies may need to evaluate one or more technology products.

Outcomes to be achieved:

1. Asses the business/organisational value of Digital Data Analytics and how to

apply methods to determine value;

2. Estimate the resource requirements when developing Digital Data Analytics

technologies, e.g. Technical skills requirements, time and financial resources

3. Construct projects of change for implementing Digital Data Analytics;

4. Evaluate Business Planning for innovation and change when applying Digital

Data Analytics in both existing organisations, or as an innovation for new startup organisations;

5. Describe trends and contemporary issues, such as privacy and security, when

applying Digital Data Analytics technologies;

6. Interpret general trends in technological and disciplinary terms;

7. Justify the idea of and key tenets of methodology to guide professional practice

to help ground the discipline of ‘Digital Analytics’.

writing Instructions

Illustrates an excellent level of understanding of complex issues

in the subject.

All requirements of the work are dealt with to a

high standard and the work is free from all but isolated minor

errors.

The material is wholly relevant to the tasks.

Excellent analysis, synthesis and critical reflection with the ability

to tackle issues and questions not previously encountered.

Evidence of independent and original judgment in relation to the

resolution of the client’s needs and problems.

데이터 마이닝 데이터 과학 Data Analytics Data Visualization Data Engineer

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