COM302 Web Analytics Topic 2


Flashcards for COM302 Web Analytics Topic 2 at Murdoch University.
Ronan Kavanagh
Flashcards by Ronan Kavanagh, updated 3 months ago
Ronan Kavanagh
Created by Ronan Kavanagh 3 months ago

Resource summary

Question Answer
Why is "Big Data" only a general term? (1) 1. Big Data means several different things owed to being a group of technologies
According to Lohr, how does Big Data change web analytics? (2) 1. Potential revolution in measurement 2. Way of thinking - How should decisions be made?
According to De Mauro, what are the four main themes of Big Data? (4) 1. Information 2. Technology 3. Methods 4. Impact
What does "information" as a theme of Big Data represent? (1) 1. The digitisation and datafication revolution that fuels Big Data
What does "technology" as a theme of Big Data represent? (4) The medium that facilitates the: 1. Collection 2. Processing 3. Transmission 4. Storage of Big Data
What does "methods" as a theme of Big Data represent? 1. Techniques used to process Big Data 2. The interdisciplinary knowledge required to understand and apply Big Data (e.g. STEM + Humanities)
What does "impact" as a theme of Big Data represent? (2) 1. The pervasive omnipresence of Big Data in our lives 2. The degree which Big Data affects our lives
Why does Big Data require technology to be interpreted? (2) 1. High Volume, Velocity and Variety makes it difficult for humans to analyse effectively 2. Technology provides analytical methods to interpret it and gain Value
What are the "Four V's" of Big Data? 1. Volume = Amount / Scale of data 2. Velocity = Speed of data generation / processing 3. Variety = Types of data (e.g. Structured, Unstructured, Semi-Structured) 4. Veracity = Accuracy and reliability of the data
Name and explain three V's besides the Four V's that could help describe Big Data Variability: Inconsistencies / Disparencies Validity: Accuracy / Appropriateness Vulnerability: Security concerns of data or its use Volatility: How long before data becomes outdated Visualisation: Representing data visually helps humans interpret it Value: What purpose / insights of data
What are the six provocations of Big Data according to Boyd and Crawford? 1. Changes the definition of knowledge 2. Claims to objectivity and accuracy are misleading 3. Bigger data ≠ Better Data 4. No context = No meaning 5. Accessible data ≠ Ethical data 6. Power of Big Data widens the Digital Divide
How can Big Data challenge our concept of what knowledge is? (2) 1. Big Data cannot be interpreted w/o technology 2. Radical shift in how we think about / do research
Why can claims to objectivity and accuracy in Big Data be misleading? (3) 1. Bias in how the data is collected 2. Bias on the forms/types of data collected 3. Bias in how the data is presented
Why does bigger data not always equal better data? (2) 1. Volume is so large that little things can go unnoticed 2. Smaller data sets and outliers can tell us things big data may overlook
Why does big data require context for it to have Value? (2) 1. Volume of data mandates explanation to understand connections between the data 2. Context grants insight into how the Value of the data can be applied
Why is accessible data not always ethical to use? Give an example. (2) 1. Researchers should be accountable towards their research subjects (e.g. informed consent) 2. Examples: Gleaning data off of public social media profiles, using identifying details gained from public records etc.
What is the Digital Divide and how can Big Data worsen it? (2) 1. Digital Divide: Advantages / Necessity of technology puts those without access to it at a disadvantage 2. Big Data holds so much power that those without it can be at a disadvantage
What are two concerns / issues that arise from Big Data? (2) 1. Privacy and increased surveillance 2. Ethical use of data 3. Worsens the Digital Divide
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