Data Governance

Increase the transparency, accountability and auditability with our data lineage features. Use metadata repositories to improve the master data management.

• Automatic data lineage
• Column-level data lineage
• Persuasive audit trails
• Column masking
• Metadata repositories

Data Modeling

Model your data with the highest flexibility and lowest maintenance efforts.

Flexible data model: Based on virtual views data models can be quickly adapted to your business needs with simple SQL.

Single source of truth: Build one central single source of truth for all your data consumers.

Rapid Prototyping: The results of testing are immediately visible, can be changed quickly and propagated company-wide.

Data Federation

In order to effectively query data across data sources, the federation engine supports a range of different optimization strategies. By default, heuristics will choose the best strategy automatically for best performance and lowest resource usage, but still leaves the option to fine-tune the behavior using query hints.

• Cross-database functions: Joins, Unions, SELECT/INSERT INTO
• Nested loop
• Merge join, dependent semi-join
• Dynamic cost-based query optimization

Automation

Automate your data workflows with Jobs and Schedules.

Jobs: Set rules for automated decision making and execute them. Automate data workflows and edit data in your data sources with the SQL queries you built.

Schedules: Set up flexible schedules and choose from a variety of scheduling options: intervals down to one minute and schedules dependent on other jobs. Gain full control with Data Virtuality’s transparent overview of all schedules and jobs.

Persistence

Materialization Algorithms: Full copy (used with materialized tables, views, joins, aggregations), Incremental replication based on timestamp/id fields (used with materialized tables and views).

Full Replication: Automated ETL to move/replicate data from a data source into a target storage.

Performance: Schedule incremental cache refreshes to boost performance or schedule full replications in a target storage.

Real-Time Data

Data Virtuality provides direct access to real-time data or historical data from your sources.

Real-Time Data: The virtual layer allows to query real-time data directly from the data source. Perform joins across multiple data sources on the fly. With the ability to write to connected data sources Data Virtuality Server enables you to trigger actions based on data.

Historical Data: You can also access historical data from your data sources and replicate it into your data warehouse.

200+ Connectors

Data Virtuality offers 200+ ready-to-use connectors.

Quick Connection: Quickly connect to your data sources by filing out the parameters in the connector wizard (5 minute setup).

Unified Data Structure: Data Virtuality transforms connected data sources to SQL tables, regardless the source file format. Join and query all data from connected data sources using SQL.

Connect Webservices

Connect to any Webservice: Access data and schedule updates from any web service (e.g. Rest API) using Data Virtuality’s CSV or XML/JSON query builder. Data Virtuality automatically applies a relational structure and enables you to modify the output format with a few clicks.

Then, easily add data from web services to your data model by creating views.

Data Virtuality Studio

The Data Virtuality Studio is the client where you can connect your data source and manage data in SQL.

• Windows / Linux / Mac (64bit)
• SQL Editor code completion on column level
• Metadata dependency viewer (data lineage)
• Metadata catalog and search
• Graphical view builder
• Wizards for easily connecting generic data using the formats XML, JSON, CSV, xSV

Business Data Shop

The Data Virtuality Web client enables all business users (depending on their permissions) to search metadata and query SQL from the webbrowser without using the Data Virtuality Studio.

• Metadata catalog and search
• Self-service data access for business users
• Write and run queries
• Download data

GDPR Compliance

Virtualized Personal Data: With the virtual layer, users do not have to physically consolidate / replicate sensitive personal data outside of the source systems.

Updated Data: The LDW allows users to get the latest, accurate information as applied in the system of record (avoiding unsynchronized / outdated copies of data).

Secured Data: The LDW enables restricted data access across the heterogeneous data sources depending on the type of user.

Security

• Row-based security
• Git integration
• Built-in user/role based permission system
• Permission granularity on schema, table, column level
• LDAP authentication (Active Directory, ForgeRock, etc)
• Versioning (history of changes) for all custom metadata
• Access to audit information and usage statistics using SQL from external tools
• Security protocols: SSL/TLS, HTTPS