Big Data Explained In 18 Minutes | What Is Big Data? | Big Data For Beginners | Simplilearn

Summary

This video explores the concept of Big Data, from its evolution to its modern-day applications. It covers the definition, types, and 5 V's (Volume, Velocity, Variety, Veracity, and Value) that define Big Data. The video also discusses its uses in various sectors such as healthcare, finance, and entertainment, and highlights the benefits and challenges of managing large datasets. Career opportunities in Big Data, key tools like Apache Hadoop, Spark, and MongoDB, and the promising future of the industry are also explored, making this a comprehensive guide for anyone interested in the field of Big Data.

Takeaways

• 😀 Big data has evolved rapidly, with the world generating 40 exabytes of data annually, and by 2021, data was being created every 40 minutes.
• 😀 Big data refers to a collection of massive, ever-growing data that is too large for traditional database systems to manage and analyze.
• 😀 The core steps of working with big data include collecting, processing, cleaning, and analyzing data to derive valuable insights.
• 😀 Big data is used in various industries, including manufacturing, healthcare, education, media, and finance, to improve decision-making and efficiency.
• 😀 There are three types of big data: structured data (organized and tabular), unstructured data (raw and unorganized), and semi-structured data (a mix of both).
• 😀 The 5 V's of big data—Volume, Velocity, Variety, Veracity, and Value—are crucial for understanding and extracting insights from data.
• 😀 Big data can improve customer experience, decision-making, cost-saving, fraud detection, and data security through its insights and patterns.
• 😀 Despite its advantages, big data comes with challenges such as the need for skilled professionals, data integration, selecting appropriate tools, and securing data.
• 😀 Career opportunities in big data include roles such as big data engineer, data scientist, data architect, and security engineer, all requiring specific technical skills.
• 😀 Tools used in big data processing include Apache Hadoop, Apache Spark, Apache Flink, Apache Storm, and MongoDB, each serving different data needs and processing speeds.
• 😀 The future of big data looks promising, with increasing job demand and high salaries, particularly in analytics and data science roles.

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