Big Data Virtualization solution provides a logical data layer that integrates enterprise data across disparate systems and manages the unified data for centralized data access. MDACA is designed to provide virtual data access to support multiple data sources and their integration with enterprise Extract Transform Load (ETL) tools.

MDACA’s main benefits include:

Support of data queries across many systems without data copy and replication, thereby bolstering master data
management and legacy data migration initiatives and reducing cost.

Operationally optimized in both Amazon Web Services (AWS) and Azure Cloud.

Offers comprehensive data abstraction, federation, integration, and transformation.

Delivers capabilities to combine data from one or multiple sources into reusable and unified logical data models accessible through standard Structured Query Language (SQL) and/or web service interfaces for virtual data utilization and sharing.

Designed to provide a single view of enterprise data while hiding the technical complexities of database types, data locations, and data transformations making it easy for business owners to understand.

Logical Data Layer

Provides a virtual approach to accessing,
managing, and delivering data.

Legacy Data Migration Support

Reduce risk of system modernization by updating
business applications while replacing legacy

Query Federation

Access data from multiple systems within a
single query.

Eliminate Data Silos

Delivers integrated information while reducing data
silos, allowing data to remain in source systems
and reducing number of data copies.

Data Management Support

Provides a centralized secure layer to catalog,
search, discover, and govern unified data and its

Advanced Query Support

Support American National Standards Institute (ANSI) Structured Query Language (SQL) semantics, including complex queries, aggregations, and sub-queries.

Data Integration

Integrates data across the enterprise systems
supporting a wide range of data formats and

Scaled to Support Business and Security Needs

Scale easily to run large queries and on-demand
clusters coupled with fine grained security and
privacy controls.

High Performance Queries

Supports highly parallel and distributed queries
built from the ground up for efficient, low latency