Day 5 - Path towards Data Engineering(Datalake challenges)#devtechie #dataengineering #datalakehouse

On Day 4, we took a deeper dive into the concept of Data Lakes — how cloud computing enabled their rise, what challenges they helped overcome, and why they became central to modern Big Data architecture. We also briefly discuss how NoSQL databases complement this ecosystem.

In this video, we explore essential components and challenges related to Data Lakes:

Data and File Formats – Understanding common file types (CSV, Parquet, ORC) and their impact on performance
Metadata Management – Why metadata is crucial for discoverability and query efficiency
Partitioning – How partitioning improves query speed and scalability in large datasets
Compaction – Techniques to optimize storage and reduce small file problems
Limitations of Data Lakes:
• The challenge of schema-on-read and inconsistent data structures
• The lack of ACID transactions, and what that means for data reliability
We wrap up with a practical conclusion, setting the stage for understanding how technologies like Delta Lake and Apache Iceberg emerged to address these gaps.

Whether you're a data engineer, architect, or curious learner, this video helps you understand the real-world considerations behind building and managing Data Lakes.

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Видео Day 5 - Path towards Data Engineering(Datalake challenges)#devtechie #dataengineering #datalakehouse канала DevTechie