Data Virtualization presents a unique approach for the Enterprises
By MYBRANDBOOK
The government is targeting an investment of Rs 3 lakh crore in the next five years as part of the hyper-scale data centre scheme and is planning to provide between 3 to 4% of capital investment as an incentive to companies, along with real estate support and faster clearances. Data centre is a big growth segment for many players, with digitisation taking off across a multitude of our lives, both personal and professional. Most of the enterprises move into the next phase of quickly accessing data without persistently storing it, there will be rapid data virtualization adoption.
Data virtualization software acts as a bridge across multiple, diverse data sources, bringing critical decision-making data together in one virtual place to fuel analytics. Data virtualization addresses the data movement challenge by ensuring data remains at the source — yet is also available for consumption in real-time for consuming applications. It provides a modern data layer that enables users to access, combine, transform, and deliver datasets with breakthrough speed and cost-effectiveness.
Data virtualization technology gives users fast access to data housed throughout the enterprise—including in traditional databases, big data sources, and cloud and IoT systems—at a fraction of physical warehousing and extract/transform/load time and cost. With data virtualization, users can apply a range of analytics—including visualized, predictive, and streaming analytics—on fresh, up-to-the-minute data updates. Through integrated governance and security, data virtualization users are assured their data is consistent, high quality, and protected.
Additionally, data virtualization allows for more business-friendly data, transforming native IT structures and syntax into easy-to-understand, IT-curated data services that are easy to find and use via a self-service business directory. Data virtualization supports multiple lines of business, and also provides a single point from which to manage and enforce data governance and data privacy protocols across multiple different data sources.
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