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The world is entering a new era of innovation. Data from sources including sensors, physical equipment, and software applications populate a proliferation of information silos that must be managed properly. The growing number of data sources that are associated with the Internet of Things and multicloud systems increases the need for robust distributed data management solutions.
Enterprises make significant investments to develop data management strategies using data warehouses, data marts, data lakes, and so on. Their goal is to improve how they integrate and analyze data. It is increasingly clear that rapid growth in the volume, velocity, and variety of available data is straining traditional strategies for data management and analysis. These challenges include:
As the volume, velocity, and variety of data sources increase, the agile enterprise must be able to mine value in a short period. The compute and storage resources required to maintain the current generation of data warehouses and data lakes have increased so that these traditional approaches are no longer practical. To address these evolving data management challenges, a solution that enables accessing data in its native repository has significant advantages, including:
Addressing these challenges allows developers and data scientists to spend more time mining data and developing insights for the enterprise and less time moving it around from one repository to the next.
Data virtualization solutions that can easily access disparate data repositories help organizations to quickly integrate with new data sources across edge, core, and cloud locations. These solutions offer the best option for broadening the value of data silos by enabling customers to gain insights. Thus, the capability to quickly integrate new data sources accelerates the ability of the enterprise to move from information to actionable insights.
Server virtualization uses a hypervisor layer to hide the complexity of hosting resources using disparate operating systems on a common platform. Similarly, data virtualization uses a “datavisor” to hide the complexity of working with many data sources. When data repositories are connected through a common virtualized access and management layer, this datavisor layer includes a library of access drivers to connect to common data repositories. The core value provided is the ability to integrate, present data, and enable analysis across different repositories with less end-user and developer complexity.
This white paper and the associated design guide show how Oracle Big Data SQL on Dell Technologies infrastructure advances the use of enterprise data virtualization technology. As part of the Oracle data virtualization journey, you will learn how Oracle Big Data SQL was installed and configured in the Dell Technologies solutions evaluation lab. We also discuss how the infrastructure components were chosen to support this solution. In the final phase of our evaluation testing, we document how a TPCH decision support dataset can be imported into different management repositories, demonstrating the value of Oracle’s Big Data SQL data virtualization approach. This white paper, together with the associated design guide, assists your enterprise in accelerating your data virtualization journey using Oracle Big Data SQL on Dell Technologies infrastructure with PowerFlex storage.