What if you could simply and easily analyze consolidated information from a sales data mart, a few spreadsheets and a big social media feed? How about the value you could gain from combining real-time customer behavior information with historical trend data from disparate sources to make instant, insightful decisions? For many IT shops, it’s a dream; perhaps a nightmare. For many modern businesses, it’s a necessity. For some market leaders, it’s the new Virtual Reality — a Data Virtualization reality.
This document describes how Data Virtualization avhieve:
- Abstraction: Business people receive a business (semantic) view of information, hiding technical complexity with an abstraction layer based on a model and metadata that describe the data
- Delivery: Using well-defined, shared data services, which allow data delivery to different users or applications in real-time as well as scheduled and cached modes
- Transformation: Based on models and metadata, individual or combined data is transformed to a common schema, addressing quality, consistency and usability requirements
- Combination: Data returned from multiple sources is joined as required in the higher-level query
- Access: Interfaces address a wide variety of sources —relational databases, spreadsheets, multi-structured formats such as documents, NoSQL and XML files as well as web pages and services.