The combination of the growing demand for analytics and the desire to take advantage of the benefits of cloud computing has inspired more organizations to modernize their enterprise environments. This modernization, though, introduces challenges in leveraging the cloud’s scalability and performance due to the complexity of developing a coherent data architecture embracing an increasing variety of data assets distributed across multiple systems, environments, and even different cloud service providers.
TDWI’s research sees a trend in addressing these challenges through the adoption of a unified environment incorporating tools to address all data management aspects of the analytics life cycle while meeting analysts’ needs for accessibility, scalability, and performance. Data virtualization, a technology that has matured over the past 20 years, provides a foundation for this unified platform.
In this talk, we discuss how the core capabilities of data virtualization are fundamental to empowering analytics consumers of varying technical expertise to access and analyze data from a variety of underlying systems. Attendees will hear how data virtualization:
- Provides an abstraction for semantic consistency
- Enables transparent federation of multiple data assets of different types
- Optimizes the execution of federated queries
- Reduces or eliminates data latency
- Speeds the delivery of analytical insights