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Big Data
Introduction to Big Data
At the end of this course, you will be able to:
• * Describe the Big Data landscape including examples of real world big data problems
including the three key sources of Big Data: people, organizations, and sensors.
• * Explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and why
each impacts data collection, monitoring, storage, analysis and reporting.
• * Get value out of Big Data by using a 5-step process to structure your analysis.
• * Identify what are and what are not big data problems and be able to recast big data
problems as data science questions.
• * Provide an explanation of the architectural components and programming models used for
scalable big data analysis.
• * Summarize the features and value of core Hadoop stack components including the YARN
resource and job management system, the HDFS file system and the MapReduce
programming model.
• * Install and run a program using Hadoop!
Introduction to Big Data: What launched the Big Data
era?
600$ pour acheter un disque dur pour
stocker toute la musique dans le monde
to buy a disk drive that can store
Introduction to Big Data: What launched the Big Data
era?
5 milliards de téléphones mobiles
utilisés
5 billion mobile phone in use in 2010
Introduction to Big Data: What launched the Big Data
era?
Introduction to Big Data: What launched the Big Data
era?
Computing
anywhere and anytime
On-Demand
Computing
Introduction to Big Data: What launched the Big Data
era?
Ère de Big Data
Flux de données
Computing
anywhere and anytime

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big data presentation to upload.pptx

  • 2. Introduction to Big Data At the end of this course, you will be able to: • * Describe the Big Data landscape including examples of real world big data problems including the three key sources of Big Data: people, organizations, and sensors. • * Explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and why each impacts data collection, monitoring, storage, analysis and reporting. • * Get value out of Big Data by using a 5-step process to structure your analysis. • * Identify what are and what are not big data problems and be able to recast big data problems as data science questions. • * Provide an explanation of the architectural components and programming models used for scalable big data analysis. • * Summarize the features and value of core Hadoop stack components including the YARN resource and job management system, the HDFS file system and the MapReduce programming model. • * Install and run a program using Hadoop!
  • 3. Introduction to Big Data: What launched the Big Data era? 600$ pour acheter un disque dur pour stocker toute la musique dans le monde to buy a disk drive that can store
  • 4. Introduction to Big Data: What launched the Big Data era? 5 milliards de téléphones mobiles utilisés 5 billion mobile phone in use in 2010
  • 5. Introduction to Big Data: What launched the Big Data era?
  • 6. Introduction to Big Data: What launched the Big Data era? Computing anywhere and anytime On-Demand Computing
  • 7. Introduction to Big Data: What launched the Big Data era? Ère de Big Data Flux de données Computing anywhere and anytime