Big Data Ecosystems: Technologies and Challenges

This lecture introduces the fundamental concepts of big data ecosystems, focusing on the technologies and challenges associated with managing large datasets. It begins with an overview of the big data landscape, highlighting the evolution of technologies from 2014 to 2023. The instructor discusses the importance of understanding the various components of big data, including data lakes, distributed computing, and the CAP theorem, which addresses consistency, availability, and partition tolerance in distributed systems. The lecture emphasizes the significance of scaling strategies, such as vertical and horizontal scaling, to effectively handle big data challenges. Additionally, it covers the differences between batch and stream processing, illustrating how each approach is suited for different types of data processing tasks. The session concludes with practical exercises on using Hadoop's HDFS for data management, including uploading, managing, and accessing data programmatically. Overall, this lecture provides a comprehensive foundation for students to navigate the complexities of big data technologies and their applications.