Techniques for Big Data Analytics

Big Data 2021
  • 12 Videos | 34m 22s
  • Includes Assessment
  • Earns a Badge
Big data analytics provides a way to turn the vast amounts of data available in today's digital world into valuable insights. For this reason, big data analytics techniques have taken a central place in many businesses' IT infrastructure. These comprise complex processes and multiple stack layers that allow you to transform raw data into visualizations that demonstrate trends or other phenomena. Use this course to explore the basic principles and techniques of big data analytics in a business context. Go through each step of data processing to fully comprehend the big data analytics pipeline. Furthermore, explore various use cases of big data analytics through real-world examples. When you're done with this course, you'll have a foundational comprehension of some of the technologies behind big data and how these can drive business decisions for the better.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    describe the challenges in the current data analytics models and system designs, such as scalability, consistency, reliability, efficiency, and maintainability
    name and describe the role of the main layers of big data analytics, from the bottom all the way to the top
    specify why unstructured data comes from variable sources and describe how it moves from its origin to storage and gets further analyzed and visualized
    define the role of the data processing layer and specify how information captured in the previous layer is processed
    define the role of the data storage layer using HDFS as an example of commonly used primary data storage
  • outline the main pillars and components of big data architecture
    describe batch processing, its use cases, and common reasons for using it
    outline how stream processing enables quick decision-making by creating actionable real-time insights
    define the concept of Lambda architecture and outline its use cases
    define the concept of Kappa architecture and outline its use cases
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 52s
    UP NEXT
  • Playable
    2. 
    Big Data Analytics Challenges
    4m 20s
  • Locked
    3. 
    Big Data Analytics Stack Layers
    2m 50s
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    4. 
    Big Data Ingestion
    4m 13s
  • Locked
    5. 
    The Data Processing Layer
    3m 36s
  • Locked
    6. 
    The Data Storage Layer
    2m 29s
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    7. 
    Pillars of Big Data Architecture
    2m 49s
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    8. 
    Batch Processing and Big Data
    2m 50s
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    9. 
    Stream Processing and Big Data
    3m 6s
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    10. 
    Lambda Architecture and Use Cases
    2m 41s
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    11. 
    Kappa Architecture
    2m 24s
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    12. 
    Course Summary
    1m 12s

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