Overview of Big Data Concepts and Applications

Jun 22, 2024

Lecture on Big Data

Introduction

  • Discussion on key points of data
  • Helpful for university exams
  • Useful for career and knowledge growth

Topics Covered

  1. Development of technology
  2. Introduction to Big Data
  3. Types of data and their examples
  4. Big Data technologies and tools
  5. Data Analytics
  6. The five Vs of Big Data
  7. Industry applications of Big Data

Development of Technology

  • Technology was limited 10-15 years ago (e.g., old mobile phones)
  • Modern times include smartphones and driverless cars
  • Internet of Things (IoT): All devices connected to the internet
  • The rise of social media and data generation

What is Big Data?

  • Very large and complex data sets
  • Definition: “A large collection of datasets that cannot be processed by traditional database tools”
  • Different types of data (text, audio, video)

Types of Data

  1. Structured Data
    • Formatted data (rows and columns, like relational databases)
  2. Unstructured Data
    • Data with no format (like MP3, MP4)
  3. Semi-structured Data
    • Mixed format (like JSON, XML)

Examples and Uses of Big Data

  • Transportation: Navigation systems
  • Advertising and marketing
  • Banking and financial services
  • Government and media

Big Data Architecture

  1. Data Source
  2. Data Storage
  3. Batch Processing
  4. Stream Processing
  5. Analytics
  6. Reporting

Five Vs

  1. Volume: Amount of data
  2. Variety: Types of data
  3. Velocity: Speed of data generation
  4. Veracity: Reliability of data
  5. Value: Utility of data

Big Data Technologies

  • Storage: Hadoop, MongoDB
  • Processing: Apache Spark
  • Mining: RapidMiner
  • Visualization: Tableau

Importance of Big Data

  • Cost savings and time savings
  • Understanding market conditions
  • Social media analytics
  • Innovation and development

Need for Data Analytics

  • Enhance business operations
  • Develop next-generation products
  • Use advanced analytics techniques

Types of Big Data Analytics

  1. Descriptive Analytics
    • What is happening currently
  2. Predictive Analytics
    • Estimating the future
  3. Prescriptive Analytics
    • What actions should be taken
  4. Diagnostic Analytics
    • Analysis of why it happened

Applications

  • Banking, communications, media, healthcare, education, government, insurance, retail, transportation

Finally, all the points covered in this video are important and will help in your exam preparation.