Data Virtuality Product Overview
Data Virtuality is a comprehensive data integration platform designed to simplify and streamline the process of accessing, integrating, and utilizing data from diverse sources. Here’s a detailed look at what the product does and its key features.
What is Data Virtuality?
Data Virtuality is a data integration company that offers a SaaS data platform leveraging data virtualization and a robust replication engine. This platform is capable of performing ETL (Extract, Transform, Load), ELT (Extract, Load, Transform), and Change-Data-Capture (CDC) operations, making it a versatile solution for various data integration needs.
Key Features and Functionality
Unified Data Access
Data Virtuality provides a unified point of access for all users, ensuring that both technical and non-technical users can efficiently access and utilize data from multiple sources. This includes SQL, NoSQL databases, REST APIs, flat files, business applications, and cloud services.
Universal Language
The platform introduces a single language for data querying and manipulation, using a built-in ANSI SQL. This simplifies the data integration process and reduces the learning curve for users, allowing them to combine data from different sources seamlessly.
Flexible Deployment Options
Data Virtuality offers various deployment options to adapt to different environments, including SaaS, self-hosted in the cloud, hybrid, and on-premises configurations. This flexibility ensures that the platform can be tailored to meet the specific needs of an organization.
Data Transformation and Integration
The platform automatically transforms nested data such as JSON, XML, and NoSQL results into a familiar row-column format. This data can then be joined using standard SQL join syntax. Users can also create views or stored procedures to reuse SQL logic and build a semantic layer within the platform.
Security and Governance
Data Virtuality implements robust security measures, including role-based security, row-level filtering, and column masking. This ensures that data is accessed and managed securely, with features for data governance, audit queries, and automation.
Performance Optimization
The platform is optimized for performance with an internal query optimizer that pushes down logic to the data source, reducing data set sizes and suggesting indexing and caching when necessary. It also supports materialization and caching of queries and data sets to improve query performance.
Connector Wizards and Data Models
Data Virtuality includes connector wizards that enable quick and easy connection to over 100 different systems. Users can create logical data models without physical data extraction, making the process flexible and agile. These models can be tested, adapted to business needs, and provided in a semantic layer using simple SQL.
Integration with BI Tools and Programming Languages
The platform supports integration with various BI tools such as Tableau and PowerBI, as well as direct access through programming languages like R and Python. Data can be exposed through JDBC, ODBC, REST APIs, and OData interfaces.
Automation and ETL/ELT Capabilities
Data Virtuality includes robust ETL and ELT capabilities, such as snapshots, append operations, incremental updates, and support for slowly changing dimensions. The platform also allows for automation of tasks like sending emails and performing data transformations.
In summary, Data Virtuality is a powerful data integration platform that simplifies data access, transformation, and governance by leveraging data virtualization, universal SQL, flexible deployment options, and robust security and performance optimization features. It is designed to meet the complex data integration needs of modern businesses, making data more accessible, usable, and secure.