Organizations no longer suffer from a lack of data; they’re suffering from lack of the right data, at the right time. Start treating your data less as a static warehouse and more as a dynamic supply chain. With a data supply chain, you get just-in-time processing capabilities that can bring together data from multiple sources, easily accommodate new data sources, and transform the data according to data consumers' needs.
Red Hat® JBoss® Data Virtualization is a data supply and integration solution that sits in front of multiple data sources and allows them to be treated as single source, delivering the needed data—in the required form—at the right time to any application or user.
Rethinking data integration
The need to simplify information is driving significant change in organizations: 43 percent of all organizations currently are making changes to how they design and deploy information
Deriving value from analytics requires organizations to prepare data for use, but today’s explosion of data volumes, types and sources makes this challenging. Moreover, information must be placed in an operational context to be acted upon. Because current integration methods cannot address all these needs, the results often are inflexible systems and data sprawl.
Now, though, data preparation tools are available that enable virtualized access to multiple data sources, making it possible to deliver information promptly and in the appropriate contexts.Download the infographic
Access data from multiple, heterogeneous data sources.
Easily combine and transform data into reusable, business-friendly virtual data models and views.
Make unified data easily consumable through open standards interfaces.
Red Hat JBoss Data Virtualization is a comprehensive platform that enables agile data use. It hides complexities, like the true locations of data or the mechanisms required to access or merge it. Data becomes easier for developers and users to work with.
Gain critical business insights by making all data easily consumable by people who need it.
- Improve the use of data assets.
- Derive more value from existing hardware and storage investments.
- Complement existing integration technologies like service-oriented architecture (SOA); enterprise application integration (EAI); and extract, transform, and load (ETL).
Model-driven graphical design and development environments let you respond faster to change and improve your staff's efficiency. Your data virtualization projects are completed faster, so you realize benefits sooner.
- Better and faster than hand-coding and physically copying and moving data
- Faster and less costly than batch data movement
- Optimized development and maintenance with loose coupling
JBoss Data Virtualization gives your organization the unified information it needs to increase revenue and reduce costs by:
- Delivering data in the right form, at the right time, to the right people.
- Providing decision support and greatly enhancing the value of business intelligence (BI) with a complete view of the information you need.
- Allowing the mixing of on-premise data with cloud data, and real-time operational data with historical information.
Data virtualization layers deliver data firewall functionality. JBoss Data Virtualization improves data quality with:
- Centralized data authentication, access control, and policy enforcement.
- Robust security infrastructure and auditing.
- Reduced risk with fewer physical copies of data.
The metadata repository catalogs enterprise data locations and the relationships between the data in various data stores, creating transparency and visibility.
Without a data virtualization strategy, you risk knowing less about your customer, delivering fewer real-time business insights, losing competitive advantage, and spending more to address data challenges.Forrester Research Learn more
Red Hat JBoss Data Virtualization lets users get the actionable, unified information they want, the way they want it, and at the speed their business needs it. Combined with ease of development, JBoss Data Virtualization allows rapid delivery for a range of IT projects and initiatives.
Data virtualization is an excellent way to expand business analytics to sources beyond those captured in existing data warehouses and data marts. This approach gives you more complete and actionable information, and faster time to solution. The rapid, iterative data abstraction and provisioning capabilities of JBoss Data Virtualization are key to a fast-paced environment where data is created and changed at varying speeds.
If your organization struggles with uncontrollable point-to-point integration, you’ll benefit from JBoss Data Virtualization. By unifying data access for analytics, JBoss Data Virtualization:
- Simplifies data access.
- Improves reuse.
- Reduces change impact.
- Achieves consistent semantics.
JBoss Data Virtualization provides user-friendly views and exposes high-quality information assets. Business users can easily access trusted data sources and perform self-service analytics using any BI tools of their choice.
Applications often need an aggregated view of data from master data management (MDM), data warehouse (DW), and other online transaction processing (OLTP) systems to gain a complete view of data in real time.
An example of this is call center apps used by agents, which need to perform full read/write transactions for various systems. The virtual data layer serves as a unified, enterprise-wide view of business information that improves the ability of users to understand and use enterprise data.
Data virtualization delivers the data services to SOA apps. It speeds the creation of data services that encapsulate the data access logic, and lets multiple business services acquire data from a centralized data layer.
Data virtualization combines SOA principles—like decoupling, reuse, and agility—with key information governance principles, such as abstraction, shared semantic models, and data standards. This lets IT build and deploy a layered data architecture in a simpler, faster, and more consistent and scalable way.
- Data virtualization provides reverse proxy access to data, keeping physical data sources anonymous. This prevents unnecessary exposure.
- Get improved data quality via centralized access control, robust security infrastructure, and a reduction in physical copies of data to reduce risk.
- A metadata repository catalogs enterprise data locations, and the relationships between the data in various data stores provide transparency and visibility.
More and more organizations have big data stored in Hadoop and NoSQL systems. But most reporting and analytical tools can't access those database servers, because most require an SQL interface. Data virtualization provides the solution by masking these sources as SQL tables.
Big data sources, like Hadoop and NoSQL, need to integrate with existing BI and operational systems. Data virtualization provides rapid virtual integration that doesn’t require replication of already "big" data sources.
Many organizations are adopting cloud computing that requires each new cloud source to be integrated with the existing IT environment. Data virtualization solves this problem, allowing enterprises to maintain a complete view of internal and external information while taking advantage of attractive cloud economics.
Our training courses are hands-on and role-based. This means students stay at their keyboards for up to 80% of a course, boosting the retention of skills they'll use every day. We offer several convenient ways to train and save, and training facilities around the world. Visit our student center to learn more, or read some training successes.
- Red Hat JBoss Data Virtualization Development (JB450)
- Learn about modeling data sources and virtual entities.
Employers notice Red Hat certifications. They know that to become Red Hat Certified Professionals, candidates must complete real-world tasks using our technologies—not just answer questions about them. Build your career by getting certified. We offer multiple exam locations and ways to train.
- Red Hat Certificate of Expertise in Data Virtualization
The Red Hat Certificate of Expertise in Data Virtualization exam tests candidates' skills and knowledge in the use of Red Hat Data Virtualization to integrate multiple data sources.
Let Red Hat Consulting help you successfully deploy Red Hat JBoss Data Virtualization. We offer flexible engagement models to help meet your IT goals. Have unallocated end-of-year budget? Consider using Consulting Units to secure resources you'll need in the upcoming year—without committing to a specific topic up front.
- Data virtualization
- Make your data work better with Red Hat Consulting.
Collaboration is a pillar of the open source community. And it’s how Red Hat approaches support. Connect to Red Hat Support to access industry-leading technical resources available in our award-winning Red Hat Customer Portal anywhere, any time.
Red Hat JBoss Data Virtualization
In keeping with the open source way, we like to keep the lines of communication open. So whether you're a customer or just interested in learning more, connect with us. We're eager to answer questions.
- Contact sales
- Our sales representatives are knowledgeable, friendly, and always ready to help.
- Find a partner
- Find a Red Hat partner that sells Red Hat JBoss Data Virtualization or related applications.
- Red Hat JBoss Data Virtualization
- Integrate with SAP using JBoss Middleware
- Turn data into actionable information with Red Hat JBoss Middleware
- Re-think Data Integration: Delivering Agile BI systems With Data Virtualization
- Red Hat and Hortonworks: Open Modern Big Data Architecture for the enterprise
- The role of data virtualization and data services in the era of cloud computing
- Red Hat JBoss Data Virtualization for financial services and insurance
- Red Hat JBoss Data Virtualization for healthcare and life sciences
- Red Hat JBoss Data Virtualization for master data management
- Making business intelligence systems more agile with data virtualization
- Enterprise democratization of big data with data virtualization
- Deploying data virtualization in business intelligence systems
- The 3 big problems with data—and how to avoid them
- Integration intervention: Get your apps and data up to speed
- Don't let Hadoop become a new data silo
- Making good decisions? Want to? Data analytics is the key.