Parallel In-Memory Processing and Data Virtualization Redefine Analytics Architectures
Speakers: Alberto Pan, CTO, Denodo
The tide is changing for analytics architectures. Traditional approaches, from the data warehouse to the data lake, implicitly assume that all relevant data can be stored in a single, centralized repository. But this approach is slow and expensive, and sometimes not even feasible, because some data sources are too big to be replicated, and data is often too distributed such as those found in cloud data sources to make a “full centralization” strategy successful.
Attend this webinar to learn:
- Why Logical architectures are the best option when integrating Big Data.
- How Denodo’s parallel in-memory capabilities with dynamic query optimization redefine analytics architectures.
- How IT can meet business demands for data much faster with Data Virtualization.
- Challenges with traditional approaches for analytics architectures.
- Overview of Denodo's parallel in-memory capabilities.
- Product Demo of parallel in-memory capabilities accelerating analytics performance.