this is my /maɪ/ blog. The world is a messy place but at least now I have a way of structuring queries about it. And let me share with you my own story or all I known about my career - technical and non-technical in the most naive way.
This article compares monolithic data lake architecture with the decentralized data mesh approach. While data lakes centralize data for easier access, they face scalability challenges. Data mesh treats data as a product owned by domain teams, enhancing agility through four key principles: domain-oriented ownership, data as a product, self-serve infrastructure, and federated governance.
This article explores the world of Big Data, covering core concepts like the 4Vs (Volume, Velocity, Variety, Veracity), key technologies including Hadoop, Kafka, and Spark, and modern architectures such as Persistent Staging Areas and real-time processing systems. It provides a comprehensive overview of the technologies that emerged to address the challenges of modern data growth beyond traditional database capabilities.
This article discusses data integration, focusing on combining data from multiple sources into a unified view for better analysis. It contrasts ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) methodologies, explaining their approaches to data handling. The article also highlights three types of ETL pushdown techniques and the concept of data orchestrators.