According to Gartner Hype Cycle for Information Infrastructure, 2012, “the Logical Data Warehouse (LDW) is a new data management architecture for analytics which combines the strengths of traditional repository warehouses with alternative data management and access strategy. The LDW will form a new best practices by the end of 2015.” It has seven major components:
- Repository Management
- Data Virtualization
- Distributed Processes
- Auditing Statistics and Performance Evaluation Services
- SLA Management
- Taxonomy / Ontology Resolution
- Metadata Management
How does DV enable the logical data warehouse?
- Repository Management – Data virtualization supports a broad range of data warehouse extensions
- Data Virtualization – Data virtualization virtually integrates data within the enterprise and beyond.
- Distributed Processes – Data virtualization integrates big data sources such as Hadoop as well as enable integration with distributed processes performed in the cloud.
- Auditing Statistics and Performance Evaluation Services – Data virtualization provides the data governance, auditability and lineage required.
- SLA Management – Data virtualization’s scalable query optimizers and caching delivers the flexibility needed to ensure SLA performance.
- Taxonomy / Ontology Resolution – Data virtualization also provides an abstracted, semantic layer view of enterprise data across repository-based, virtualized and distributed sources.
Obviously the DV vendors are not completely there yet. But when you evalucate them, check to see if these are in its roadmap … I recommand Composite, not only the others components met our expectation, most importantly it scores high in #5 - which is important for data warehouse technology.