Cloud Data Warehouse Modernization

The economic model and elegance of cloud environments are motivating companies to assess their existing on-premises data warehouses and modernize their enterprise information environments. However, confusion about what is meant by “modernization” has led some to believe that “lifting and shifting” their on-premises implementation to a cloud environment is the default approach. In these cases, the results are mixed—while the system has technically been moved to a modern cloud platform, by no means is it modernized.
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Spotlight

OTHER ON-DEMAND WEBINARS

How to Gain a Crisis Advantage with Real-Time Information

To reduce the impact of an unfolding crisis, companies need a clear, accurate and early line of sight into emerging risks. Leaders can then act with confidence and seize opportunities to preserve brand reputation while driving operational excellence. To demonstrate how real-time information can help companies gain advanced warn
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Eliminating Data Silos: Modern Data Architectures for Analytics

Modern data applications and analytics rely on a wide variety of data both inside and outside the company; organizations depend on enriched data sets for better insights. This need, in part, has driven many companies to move to cloud data warehouses and cloud data lakes. However, it’s no longer simply about migrating to the cloud. It’s about modernizing using a combination of industry-leading services in the cloud and cloud-native data management services to deliver better business decisions, faster.
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Sharing and Deploying Data Science with KNIME Server - February 2019

KNIME

You’re currently using the open source KNIME Analytics Platform, but looking for more functionality - especially for working across teams and business units? KNIME Server is the enterprise software for team based collaboration, automation, management, and deployment of data science workflows, data, and guided analytics. Non experts are given access to data science via KNIME Server WebPortal or can use REST APIs to integrate workflows as analytic services to applications, IoT, and systems.
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Delivering Real-Time Business Insights from ERP Data in the Cloud

Businesses succeed when they can extract more contextual, relevant, and predictive insights from ERP data in real time. ERP analytics can deliver more powerful data-driven insights if deployed in a cloud-based platform. The scalability of cloud-based data repositories—such as data lakes and data warehouses—can allow more users to concurrently query, explore, correlate, analyze, and visualize more ERP data more rapidly than would be possible on many on-premises analytics platforms.
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