Lecture 2: Big Data Analytics Applications Flashcards

1
Q
6 Challenges of Big Data Analytics:
1. Data [.]:
- capture, store & process data
2. Data integration: combine data cheaply & quickly
- ensure data is [.] in terms of time period & structure
3. Processing capabilities: 
process data quickly as it's captured (i.e. [..])
4. Data [.] : 
security, privacy, access, ...
5. [.] availability (data scientist...)
6. Solution [.] 
- ROI [i.e. ...]
A

6 Challenges of Big Data Analytics:
1. Data VOLUME:
- capture, store & process data
2. Data integration: combine data cheaply & quickly
- ensure data is CONSISTENT in terms of time period & structure
3. Processing capabilities:
process data quickly as it’s captured (i.e. STREAM ANALYTICS)
4. Data GOVERNANCE:
security, privacy, access, …
5. Skill availability (data scientist…)
6. Solution cost: - Return on Investment (ROI)

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2
Q

Business Problems addressed by Big Data Analytics: Examples:

  1. Process [.] & [.] reduction:
    e. g. Smart supply chain: products produced & delivered to customers automatically
  2. [.] management:
    e. g. Amazon marketing used retina tracker to track & test user experience on their website.
  3. [.] maximisation, [.]-selling/ [.]-selling
  4. Enhanced [.] experience
  5. Customer recruiting
  6. Improve customer service:
    e. g. Amazon experiment delivery robots
  7. Identify new [.] & [.] opportunities
    e. g. Google searches
  8. [.] management
  9. [.] compliance
A

Business Problems addressed by Big Data Analytics: Examples:

  1. Process efficiency & Cost reduction:
    e. g. Smart supply chain: products produced & delivered to customers automatically
  2. Brand management:
    e. g. Amazon used retina tracker to track & test user experience on their website.
  3. Revenue maximisation, cross-selling/ up-selling
  4. Enhanced customer experience
  5. Customer recruiting
  6. Improve customer service:
    e. g. Amazon experiment delivery robots
  7. Identify new products & market opportunities
    e. g. Google searches
  8. Risk management
  9. Regulatory compliance:
    e. g. GDPR
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3
Q

Big Data technologies:
[.] : store data & process data instantly
Tableau: good at [.]
…etc.

A

Big Data technologies:
Hadoop: store data & process data instantly
Tableau: good at visualisation

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4
Q

Disruptive Technologies:

  1. Virtual Reality (VR): e.g. [.]
  2. Robotic Process Automation (RPA)
  3. Blockchain & Smart contracts
  4. AI
  5. [..] (DL)
  6. […] (IoT)
  7. Social Media
  8. Cloud Computing
  9. E-commerce
A

Disruptive Technologies:

  1. Virtual Reality (VR): e.g. HOLOGRAMS
  2. Robotic Process Automation (RPA)
  3. Blockchain & Smart contracts
  4. AI
  5. Deep Learning (DL)
  6. Internet of Things (IoT)
  7. Social Media
  8. Cloud Computing
  9. E-commerce
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