Hybrid — A Perfect Modern Data Warehouse

A modern data warehouse architecture is designed to efficiently manage, process, and analyze vast amounts of structured, semi-structured, and unstructured data. The architecture has evolved to support cloud-native platforms, real-time analytics, and AI-driven insights.

🏷️A Hybrid Modern Data Warehouse is a flexible architecture that combines both on-premise and cloud components, allowing organizations to leverage the best of both environments for data storage, processing, and analysis. It provides the ability to integrate multiple data sources, process data at scale, and generate real-time or batch insights, while maintaining cost-effectiveness, data security, and compliance.

🏷️A Hybrid Modern Data Warehouse architecture provides the scalability, flexibility, and performance required for modern data analytics, supporting real-time insights, machine learning, and big data processing across various industries.

Below is a typical modern data warehouse architecture consisting of several layers, technologies, and components:

🕹️Data Sources (Ingestion Layer): The ingestion layer focuses on bringing in data from various sources, including:

• Structured Data: Data from transactional databases (e.g., SQL Server, MySQL, Oracle) and it uses pre-defined data models filled with labels, numbers and values and is stored in relational databases (RDBMS), CRM, ERP systems, and Excel/CSV files.
• Semi-Structured Data: Semi-structured…