Data lakes are en vogue, especially when you based it on avant-garde in-memory technologies such as Spark. However, these investments don’t deliver the anticipated benefits when they are not properly governed.
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Gaining an enterprise view of the data across different independent lines of businesses is difficult when the operations, systems, and data are inherently siloed. VSP Global is integrating the silos using a semantic data layer.
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Modernizing a data warehouse is no easy task. Digital Realty successfully accomplished this goal by using a data abstraction layer supported by real-time data virtualization. Now they are expanding this abstraction layer to support a MDM project to create a 360-degree of their customers.
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Security can be a key concern when data is spread across multiple systems residing both on-premise and on the cloud. Asurion has leveraged data virtualization to use it as a single engine for security control over the data sources.
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Business intelligence is a critical requirement for understanding business operations and taking timely decisions to stay competitive. However, it can be a challenge if business has to depend on IT to customize the reports every time, thus delaying the timely availability of insights. Self-service BI is needed to address this issue.
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Many firms are adopting “cloud first” strategy and are migrating their on-premises technologies to the cloud. Logitech is one of them. They have adopted the AWS platform and big data on the cloud for all of their analytical needs, including Amazon Redshift and S3.
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See how Intel built a modern data architecture with data virtualization at its core for not just one, two, or three projects but a host of them that span the entire enterprise and support important business operations such as supplier lifecycle management.
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