Every few years, a technology emerges that fundamentally changes how we think about data processing. MapReduce did it in 2004. Apache Spark did it in 2014. And after spending two decades building data pipelines across enterprises of every size, I’ve learned that the difference between a successful Spark implementation and a failed one rarely comes… Continue reading
Tag: Delta Lake
Building the Modern Data Stack: How Spark, Kafka, and dbt Transformed Data Engineering
The data engineering landscape has undergone a fundamental transformation over the past decade. What once required massive Hadoop clusters and specialized MapReduce expertise has evolved into a sophisticated ecosystem of purpose-built tools that work together seamlessly. Having architected data platforms across multiple industries, I’ve witnessed this evolution firsthand and can attest that understanding how these… Continue reading
Azure Databricks: A Solutions Architect’s Guide to Unified Data Analytics and AI
The convergence of data engineering, data science, and machine learning has created unprecedented demand for unified analytics platforms that can handle diverse workloads without the complexity of managing multiple disconnected systems. Azure Databricks represents a compelling answer to this challenge—a collaborative Apache Spark-based analytics platform optimized for the Microsoft Azure cloud. Having architected data platforms… Continue reading
Data Lakehouse Architecture: Bridging Data Lakes and Data Warehouses
After two decades of building data platforms, I’ve witnessed the pendulum swing between data lakes and data warehouses multiple times. Organizations would invest heavily in one approach, hit its limitations, then pivot to the other. The data lakehouse architecture represents something different—a genuine synthesis that addresses the fundamental trade-offs that forced us to choose between… Continue reading