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Big Data
Big Data Training Content
Khurram M. Pirzada
Big Data & Hadoop Lead @
Allied Consultants
Introduction to Big Data
What is Big Data?
Why, where, and when of Big Data
Differentials
Potentials
Risks
Future
Case Study
What is Big Data?
Highly voluminous, complex, fast and noisy
Conventional techniques very costly
Term encompasses many domains
No single standard framework
Investment constraints real or perception?!
Different models for various functions
How not to fall in trap of buzzwords
Why, Where, When of
Big Data
It qualifies 4 components mentioned
Its all around us: twitter, Facebook, cars..
Business need insight for strategic decisions in near real-time
Industrial internet prime example
Differentials
How to identify big data from “other” data?
Can they co-exist?
Who benefits from whom?
Does one technique support other?
Potentials
Manufacturers are early adopters
Integrated eGov is for C2G facilitation
Big data and IoT: match made in heaven ;)
Operational insight that matters
Risks
Nothing is without inherent risk
Inter-”anything” protocol communication
Tracking & managing audit trail
Potential under-estimation vs over-expectations
Unwarranted data solicitation
Complex Event Processing Engines?!?!
Future
Don't we all “love to predict” :)
Big data is like Mark Sinclair (VD) or Jason Bourne (MD)
Already more innovation coming the way
Process automation visualization holds key
Business intelligence shall dominate
Specialist hardware coming soon
Which side of the spectrum are YOU ?!?!
Case Study
Purpose: get inside to business, operational and technical issues
Raise questions and offer alternate & better practical solution

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Hadoop Big Data Training (Part 1)

  • 1. Big Data Big Data Training Content Khurram M. Pirzada Big Data & Hadoop Lead @ Allied Consultants
  • 2. Introduction to Big Data What is Big Data? Why, where, and when of Big Data Differentials Potentials Risks Future Case Study
  • 3. What is Big Data? Highly voluminous, complex, fast and noisy Conventional techniques very costly Term encompasses many domains No single standard framework Investment constraints real or perception?! Different models for various functions How not to fall in trap of buzzwords
  • 4.
  • 5. Why, Where, When of Big Data It qualifies 4 components mentioned Its all around us: twitter, Facebook, cars.. Business need insight for strategic decisions in near real-time Industrial internet prime example
  • 6.
  • 7. Differentials How to identify big data from “other” data? Can they co-exist? Who benefits from whom? Does one technique support other?
  • 8.
  • 9.
  • 10.
  • 11. Potentials Manufacturers are early adopters Integrated eGov is for C2G facilitation Big data and IoT: match made in heaven ;) Operational insight that matters
  • 12.
  • 13.
  • 14. Risks Nothing is without inherent risk Inter-”anything” protocol communication Tracking & managing audit trail Potential under-estimation vs over-expectations Unwarranted data solicitation Complex Event Processing Engines?!?!
  • 15.
  • 16.
  • 17. Future Don't we all “love to predict” :) Big data is like Mark Sinclair (VD) or Jason Bourne (MD) Already more innovation coming the way Process automation visualization holds key Business intelligence shall dominate Specialist hardware coming soon Which side of the spectrum are YOU ?!?!
  • 18.
  • 19.
  • 20.
  • 21. Case Study Purpose: get inside to business, operational and technical issues Raise questions and offer alternate & better practical solution