As more companies are face the challenge of accessing and sharing the massive amount of disparate data at greater speeds, the traditional integration methods including Extract Transform and Load (ETL), Enterprise Application Integration (EAI) and Enterprise Service Bus (ESB) has become costly and inefficient. Did you know that 80% of the work is spent in preparing the data? (Forbes)
Do you need Data Virtualization (DV)?
- Is data prep time delaying your business’ ability to make decisions and take advantage of opportunities?Data Virtualization is ideal for situations where data demands change quickly and where access to the data in real time could be critical to business outcomes
- Is your data dispersed and does some of it reside outside your firewall or the cloud? Data Virtualization provides access to all of your data sources, allowing you to federate and align all of these sources into a single consumable data model
- Are regulations & security concerns preventing you from gaining access to important data when and where you need? Data Virtualization hurdles over some of these challenges because it leaves the data at the source while providing federation with other sources and virtual access from anywhere.
- Are infrastructure and maintenance costs for data warehousing and storage too high?Because we don’t create duplications of data with Data Virtualization, you eliminate most of the costs associated with traditional data management
If you answered yes to one or more of these questions, then you needed Data Virtualization yesterday
Ok, so what is Data Virtualization (DV)?
In a nutshell, Data Virtualization is a quicker/easier way to integrate, federate and transform data from multiple data sources into a single unified environment. When leveraged properly it is a “comprehensive integration strategy… (that) limits data silos and address(es) new… operational opportunities through flexibility in data access.” – Senior Research Analyst at Gartner To read full article (Click Here )
The data can then be easily accessed or shared by other applications, without being replicated: resulting in real-time on-demand access to a “virtual” data layer.
Most importantly it can leverage any existing Data Warehouse or Big Data infrastructure already in place and begin from there to be applied in situations where duplication and replication of data just don’t make any sense.
Benefits of DV
- Quickly combine multiple data sources as query-able services
- Improve Productivity in IT and by business data users (50%-90%)
- Accelerate Time-to-Value
- Improve quality and eliminate latency of data
- Reduce Costs – remove the costs associated with populating and maintaining Data Warehouse
- Significantly reduce the need for multiple copies of any data
- Less hardware infrastructure (lower costs and maintenance
Additional DV Benefits with EE
- Single Integrated Development Environment to configure, test, deploy, and monitor data virtualizations
- Fastest Time-to-Value in the market
- Accelerate Time-to-Value
- Incorporates Agile ETL also, which means leveraging the federation capabilities and logic for ETL to physically populate a destination.
- Data validation
- End user awareness and security using multiple security models
- Proprietary AppComm™ that communicates live directly and natively between the endpoints and the Transformation Engine
- Ability to write back to sources. Full CRUD (create, read, update, write) with security and transaction assurance (rollback)
- Multiple User Constituencies (Business Analysts, Developers, DBAs)
- Bi-Directional Data Access
- Reuse DV Federation Capabilities for ETL, EAI, ESB
- One Click Generation and Hosting of Web Services (REST, SOAP, JSON, OData, ADO.Net, JDBC, ODBC, BCS, BDC)
Examples of when Data Virtualization (DV) is suitable
Mergers or Acquisitions
BA & BI