A logical data warehouse (LDW) is a modern data architecture that provides a unified view of data from different sources, without physically consolidating the data in a single repository. Instead, the LDW uses virtualization techniques to create a logical layer that abstracts and integrates the data from various sources.
The main goal of an LDW is to provide business users with a single, consistent view of data, regardless of where the data resides. This helps to eliminate data silos and enables organizations to make more informed decisions based on the most accurate and up-to-date information available.
Some of the key features and benefits of an LDW include:
Data integration: An LDW integrates data from multiple sources, including traditional databases, data warehouses, data lakes, and cloud-based data stores.
Data virtualization: An LDW uses data virtualization techniques to create a logical layer that abstracts and integrates the data from various sources, without physically consolidating the data.
Real-time data access: An LDW provides real-time access to data, enabling organizations to make faster and more informed decisions.
Data governance: An LDW provides centralized data governance capabilities, making it easier to enforce data policies and standards.
Scalability: An LDW is designed to be highly scalable, allowing organizations to handle large volumes of data as their needs grow over time.
Agility: An LDW enables organizations to quickly adapt to changing business requirements by providing a flexible and agile data integration architecture.
In summary, an LDW is a modern data architecture that provides a unified view of data from different sources, using virtualization techniques to create a logical layer that integrates the data. It provides benefits such as data integration, data virtualization, real-time data access, data governance, scalability, and agility.