Overview of CData Virtuality
Turn your disparate data into real-time business insights faster with the use of data virtualization. CData Virtuality allows you to unify your cloud, application, and on-premises data seamlessly, without the need for moving and duplicating data.
CData Virtuality offers the following benefits, described below.
Real-time Data Access
CData Virtuality provides real-time access to over 300 data sources, from legacy systems to digital platforms. It has the power of CData’s connectors behind it, providing a complete, unified view of data from all sources, eliminating data gaps. When you query a virtual table or view, CData Virtuality fetches the data on demand from the source, without duplicating the data.
Semantic Layer
A semantic layer is a virtual framework that sits between your raw data and the tools that use it, such as business intelligence tools and AI. It simplifies the complexity of your data by standardizing data definitions and ensuring consistent business logic across analytics tools, so that data appears consistent regardless of its origin.
Centralized Data Governance
When data is unified via the semantic layer, centralized data governance is easier to achieve. With centralized data governance, you can ensure that your data adheres to your organization’s policies and procedures without inconsistencies or duplicate efforts.
Massively Parallel Processing (MPP)
MPP capabilities means that CData Virtuality can effortlessly manage complex analytical queries and data-intensive workloads across multiple nodes. It does this by breaking down a large query into subqueries, running the subqueries in parallel, and then combining the results. For more information about MPP, see Massively Parallel Processing (MPP) Component.
“Talk to Your Data” AI Engine
CData Virtuality’s AI engine enables users to interact with their data using natural language. This allows non-technical users to access data independently, without writing SQL or knowing the database schema. You can simply ask, “What were our top five products by revenue last quarter?” and the AI engine analyzes the question, creates a SQL query, and runs the query across all needed sources.
Query Optimization
The query optimization feature of CData Virtuality helps you improve query performance when integrating and querying data from multiple, distributed sources. It uses a cost-based optimizer to determine the most efficient query execution plan, considering factors such as table size and data distribution. It performs smart caching of query results and intermediate calculations, reducing redundant calculations for recurring queries. Frequently queried or complex views can be materialized (saved like a physical table) to improve performance. Query hints allow you to influence the query optimizer to change how queries are executed. For example, you can force the order in which joins are executed or force the query to use a specified materialized view.
For more information on query optimization and other performance optimization features, see Performance Optimization.
CData Virtuality is an enterprise-grade independent semantic layer to unify data access across the organization with a centralized, governed layer that connects heterogeneous data sources, supports rapid prototyping to test new requirements, and accelerates the delivery of data products-all to empower self-service and faster insights. Its key benefits are as follows:
Real-time access to 300+ data sources, from legacy systems to digital platforms
Centralized control for data quality,ecurity, and compliance
Seamless integration across hybrid- and multi-cloud environments
Optimized for complex analytical queries and data intensive workloads