INFS 5095 Big Data Basics Assignment

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Reference no: EM132528910 , Length: word count:2500 + 10 slides

INFS 5095 Big Data Basics - University of South Australia

Assignment

Management Proposal - Big Data Capabilities

About this Assignment
This assignment is giving you practice in bringing together the knowledge you have acquired in this course, applying it to a business need and being able to communicate that. Imagine that you are presenting your proposal to the senior management team of your chosen organisation. Assume that the audience know little about big data, but they want to make better use of their data which is why you have been invited to submit a proposal.

However, the assignment is not just a sales pitch - you must demonstrate that you know what you are talking about, back up your arguments with evidence, communicate new concepts and demonstrate to the audience that you would be worth engaging.
You are being assessed on demonstrating your understanding and applying it, not just finding and
presenting information of ‘experts'. This assignment requires you to work things out yourself as well as making use of research.

Business priority questions
Consider what questions would need to be answered to understand the key priority. See the Microsoft resources around the questions ‘Is big data the right solution?' and ‘Determining analytical goals‘ here:

Information and data sources
From the questions to be answered you need to identify the information needed and the data sources that information would come from. It may be that some of the data would not exist (that you know of) so you would be recommending that it be collected. Information and data can be explained in ‘customer sentiment from social media'. Also explain the categories of data (see ‘Big Data Analytics - Overview and Challenges').

Big data technologies
Once you know the information needed and where it would come from time to decide which big data technologies would be needed to capture, store, process, clean, share, visualise and use. This should include the end user application - would it be a predictive app? Or something else?

Provide brief explanations of the technologies required to deliver the big data capability and an example of each one technology (eg: processing of streaming data - Apache Spark). The technology choices will depend on the data types of your information.
Don't focus on a specific tool or vendor. You can use the Big Data/AI Landscape diagram that we have been looking at in Week 1 and other weeks to investigate and recommend technologies.

High Level Architecture
Your proposal should include a diagram of a high-level architecture showing the different technologies and how they fit together. This, once again, is intended for a non-technical audience. Here is an example from the workshop presentations:

Big data visualisation examples
Provide two examples (screen shots) of big data visualisations to give the audience an indication of what you would be providing them (or if you had built a prototype). Explain the visualisations. The more relevant to the business priority and organisation the better. Importantly, the visualisations should be clearly based on big data, not small data.

Big data adoption challenges
Finally include recommendations for how to address the challenges of big data adoption and big data analytics. See the ‘Big Data Fundamentals - Benefits, Challenges, Management and Skills' and ‘Big Data Technologies - Information Quality and Data Governance' and ‘Big Data Analytics - Overview and Challenges‘ topics for ideas. The recommendations should also include recommendations for dealing with quality and privacy.

Structure
PowerPoint Slide Show
The presentation slides should be a summary of the proposal covering all the areas to be included in the written proposal. Condensing complex information into dot points and deciding what to include and not what to include can take some time. Make use of visuals or diagrams to explain concepts.
There is no template provided for this part (intentionally) so choose your own template.
• There should be exactly 10 slides in the presentation file, including 1 title/introduction slide.
• Where you have used references, they should be included either as footnotes or at the end, but still within the 10-slide limit (the reference list is not included in the word count).
• Feel free to make use of animations and slide transitions - the presentation should be interesting and engaging to watch.
• Links to other sites can be included, but they won't be viewed as part of the marking.
• The presentation must be submitted as a PowerPoint presentation file (no PDF).
• It's recommended to have a look for resources around good presentation design.

Attachment:- Big Data Capabilities.rar

Reference no: EM132528910

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