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Implementing Data Virtualization for the First Time

Data Virtualization

Data virtualization is a powerful data integration and data management approach, but if you are implementing data virtualization for the first time, it helps to know how to overcome some typical challenges. In this post, I’ll outline some of the.

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A comparative assessment of digital transformation in Italy

CIO Business Intelligence

The challenge of digital transformation projects lies not so much in the technological implementation, but in the operational change required of people and the entire business organization,” he says. The data platform and digital twin AMA is among many organizations building momentum in their digitization.

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AI transforms the IT support experience

IBM Big Data Hub

Product-embedded or online support tools, such as virtual assistants, can drive more informed and efficient support interactions with client self-service. Those who implement self-service search into their sites and tools can become exponentially more powerful with generative AI.

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Conversational AI use cases for enterprises

IBM Big Data Hub

This class of AI-based tools, including chatbots and virtual assistants, enables seamless, human-like and personalized exchanges. DL models can improve over time through further training and exposure to more data. Today, people don’t just prefer instant communication; they expect it.

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DataOps Enables Your Data Fabric

DataKitchen

Industry analysts who follow the data and analytics industry tell DataKitchen that they are receiving inquiries about “data fabrics” from enterprise clients on a near-daily basis. Gartner included data fabrics in their top ten trends for data and analytics in 2019. What is a Data Fabric?

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How DataOps is Transforming Commercial Pharma Analytics

DataKitchen

DataOps has become an essential methodology in pharmaceutical enterprise data organizations, especially for commercial operations. Companies that implement it well derive significant competitive advantage from their superior ability to manage and create value from data.

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Run interactive workloads on Amazon EMR Serverless from Amazon EMR Studio

AWS Big Data

You can now use EMR Serverless applications as the compute, in addition to Amazon EMR on EC2 clusters and Amazon EMR on EKS virtual clusters, to run JupyterLab notebooks from EMR Studio Workspaces. They assign EMR Studio administrators who manage setting up EMR Studios and assigning users to a specific EMR Studio. Choose Next.