| Definition |
Centralized repository for integrated, historical, and large-scale data from various sources. |
Subset of a data warehouse, containing specific data for a particular business unit or department. |
| Purpose |
Supports enterprise-wide reporting and analytics. |
Focused on addressing the needs of a specific business unit or department. |
| Data Scope |
Stores vast amounts of data from multiple sources and business areas. |
Contains a subset of data, typically related to a single business function or department. |
| Data Integration |
Integrates data from various sources, including ETL (Extract, Transform, Load) processes. |
Contains data specific to a particular business area, often with simpler integration requirements. |
| Granularity |
Contains detailed and summarized data for extensive analysis. |
Typically contains more detailed, granular data relevant to its specific business area. |
| Performance |
Designed for complex queries and high-performance analytics. |
Optimized for quick retrieval and reporting specific to its designated business area. |
| Maintenance |
Requires significant maintenance and resources due to its size and complexity. |
Easier to maintain and manage due to its smaller size and focused scope. |
| Scalability |
Scales to handle large volumes of data and complex queries across the enterprise. |
Scalable to meet the needs of a particular business unit or department. |
| Accessibility |
Accessed by users from various departments across the organization. |
Primarily accessed by users within the specific business unit or department. |
| Data Governance |
Typically has a centralized data governance strategy and standards. |
May have its own data governance practices tailored to its specific business needs. |
| Cost |
Often more expensive to build and maintain due to its size and complexity. |
Generally less expensive to build and maintain compared to a full data warehouse. |
