The Big Data Architecture Blueprint
Summary
This article outlines a practical blueprint for building enterprise big data platforms. It explains core architectural patterns such as data lake, data warehouse, Kappa architecture, data mesh, and event-driven systems. It also covers storage approaches including sharding, replication, object storage, and columnar storage, along with integration patterns like ETL, ELT, CDC, and data federation. The examples show how teams can use Kafka, Spark, Databricks, Snowflake, and dbt to support real-time analytics, governance, and cloud reporting. The piece is mainly an educational architecture guide for data and analytics teams.
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