Big data technologies and data visualisation

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Reference no: EM132846418

Big Data Analysis

Book: Wexler, S., Shaffer, J. & Cotgreave, A 2017, The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios, 1st edn, Wiley and Sons, Hoboken, New Jersey. (ISBN 978 11192 82716)

2. Assess and adapts contemporary and innovative data visualisation approaches to gain insight and value that support effective data-driven decision-making;

3. Appraise and present complex and big data in visual from that is readily understandable by specialist and non-specialist audiences using data visualisation methods tools and techniques;

4. Interact and collaborate effectively in teams to design and implement data visualisation project;

Assignment 2 consists of ‘Three Tasks'.

TASK LIST

Topic: Queensland Road Traffic crashes by Location data set from January 2001 through to December 2016

(Pleas find the Data sets attached to this document.)

Distinct views of data visualization dashboard:
1. Count of Crash severity by Location and year.
2. Severity of crash by hour of day when crash occurred.
3. Type of crash by speed limit at crash location.
4. Count of Crash severity by speed limit, condition of road surface, atmospheric conditions and Condition of Lightning.
5. Counts of units involved in crash by location of crash.

Task 1: Big data technologies and data visualisation (20 Marks, 1000 words)

Task 1.1: Identify and describe two opportunities and two challenges that big data presents for data visualisation (10 marks, 500 words).

Task 1.2: Explain how Hadoop and MapReduce as big data management technologies might play a key role in addressing opportunities and challenges of big data visualisation (10 marks, 500 words).

Task 2: Big Data Visualisation Key Principles and Approaches (30 Marks, 1500 words) Discuss the key principles and approaches to data visualisation that your team will use in your Big Data Visualisation project. Ensure your discussion includes one or more of the challenges that organisations face in undertaking a big data visualisation initiative. And you should emphasise the importance of Data Story Telling.

Task 3: Big Data Visualisation Project with Tableau (30 marks, 500 words)

Task 3.1: Provide a data dictionary (Variable, Data Type, Description) for the data set chosen for your Big Data Visualisation Project in a

Table 3.1 with Caption: Data Dictionary (File name) and provide a short accompanying explanation of the purpose of each variable in your Big Data Visualisation Project. This will require some desktop research to understand business context of your chosen (file name) data set (250 words 15 marks)

Task 3.2 Describe your planned Tableau dashboard based on your chosen (file name) data set including four preliminary views that will be fully implemented in Assignment 3. Include screenshots of those four preliminary Tableau views, the packaged Tableau workbook file that uses your chosen data set (250 words 15 marks)

Task 4 Big Data Visualisation Project Team Journal (10 Marks 500 words)

Attachment:- Big Data Analysis.rar

Reference no: EM132846418

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Big data technologies and data visualisation : Big Data Analysis - Queensland Road Traffic crashes by Location data set from January 2001 through to December 2016

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