There is a pressing need within organizations to have faster access to data for Analytics, Business Intelligence (BI) and Reporting. The digital disruption is creating a new data ecosystem on top of traditional Data Warehouse' (DW) like Hadoop, Cloud/SaaS, Enterprise Applications, No SQL and many others, resulting in information in silos within organization units. This is where it becomes critical that the future data integration systems have enablement towards Virtualized and Unified business views of data providing the right information to the right user at the right time.
Corporates are looking for ways to leverage disparate data created during the journey of transformation for better decision making, advanced analytics and new applications. Hence, it becomes absolutely necessary to have a simple access to the data that provides a 360° unified view of the customer, product and employee data on a real time basis. Data Virtualization (DV) offers the complete capability with a single product to deliver data access, data management and data services delivery. It will help realize value from data, minimize replication and facilitates reusable Unified Data Services with powerful and agile enterprise class systems.
The data virtualization market is growing fast as enterprises increasingly consider data virtualization as a way to address the demand of trusted and secured data in real time. As per the recent market trend, growth is partly due to enterprise architects' increasing trust of data virtualization providers to act as strategic partners, advising them on key decisions. There are many enterprise product partners who are reviving their data virtualization strategy and their product on this. There are also new leaders co-existing in the market like Denodo, Stonebond etc. As the enterprises move into next phase of quickly accessing data without persistently storing it, there will be rapid data virtualization adoption.
Many argue that data virtualization will diminish the importance of ETL processes significantly but the fact is that almost 100% of data virtualization adopters are also using ETL and continue using the both effectively. On one hand, ETL is needed for large and bulk movement of data while data virtualization is needed for faster access to data. Both are critical to achieve the broader goals of an organization in analytics, BI and reporting. Companies delaying the adoption of DV are losing out. Companies dealing with huge amount of data are especially investing in data virtualization. DV has really turned the tide in the field of data management and has become a realistic practical approach.
As the Big Data revolution picks up, it becomes imperative to reduce the data repository cost and gain a competitive edge by being more agile, timely and responsive to changes. This is where data virtualization will become main stream to answer the data needs of corporates.