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Data virtualization is distinct from other data integration approaches as it is implemented through a layer of abstraction that changes the paradigm of data integration:
Connecting to data systems using a unified virtualization platform like Oracle Big Data SQL has benefits for many use cases. Perhaps the most impactful benefit is the ability of both developers and data scientists to use a common virtualization interface for analytics based on a large and growing set of data source options. Centralizing access to multiple data sources using one standard interface can result in greater efficiencies and less operational complexities.
The goal of this solution is to demonstrate the advantages of using data virtualization with Oracle Big Data SQL. We show how to efficiently access data from multiple sources without introducing extract and load overhead. Our focus is to demonstrate the functionality of Oracle Big Data SQL using moderately sized sample datasets. Showing how Oracle Big Data SQL can scale to petabytes of source data is beyond the scope of this solution. Customers interested in proof-of-concepts with larger data volumes can contact our Customer Solutions Center. Organizations using Oracle Big Data SQL will realize many benefits including improving the speed and flexibility of analytics and reporting without having to incur the overhead of moving data.
Organizations adopting data virtualization might also reduce the need for expanding existing platforms by switching from a complete dependency on structured data repositories and data lakes with a shift to using data at its source. For data scientists, this can lead toward a more a self-service oriented analytics approach. Many organizations find enabling more end users with the ability to explore data sources improves discovery of hidden insights and provides a better understanding of what is available in existing data sources. This can also lead to improved collaboration between IT and end users on the development of new business intelligence and insights. Overall, data virtualization provides many opportunities to increase agility across data analytic efforts with the express goal of improving business decisions.
In this solution, we designed an elastic server and storage solution that can be used for data virtualization and to consolidate disparate data sources. To facilitate an elastic private cloud solution, Dell Technologies used the combination of compute nodes with VMware vSphere virtualization and PowerFlex software-defined storage. This elastic private cloud solution is designed to provision resources based on the needs of data virtualization, meaning that growth can be addressed incrementally. A right-sized data virtualization solution t is neither over-provisioned or under-provisioned. Throughout this solution, we describe considerations that you can use to drive success in architecting a data virtualization infrastructure.