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Slide 1: This slide introduces Data Architecture. State Your Company Name and get started. Slide 2: This slide shows Important Technologies of Data Architecture with imagery to go with.
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Recently, there has been much hype around new design patterns that promise to deliver this much sought-after agility. In this webinar, Chris Bergh, CEO and Head Chef of DataKitchen will cut through the noise and describe several elegant and effective data architecture design patterns that deliver low errors, rapid development, and high levels.
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Six shifts to create a game-changing data architecture We have observed six foundational shifts companies are making to their data-architecture blueprints that enable more rapid delivery of new capabilities and vastly simplify existing architectural approaches (exhibit).
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This session discusses the different Big Data Architectures which have evolved over time, including traditional Big Data Architecture, Streaming Analytics architecture as well as Lambda and Kappa architecture and presents the mapping of components from both Open Source as well as the Oracle stack onto these architectures.
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A data architecture describes how data is managed--from collection through to transformation, distribution, and consumption. It sets the blueprint for data and the way it flows through data storage systems. It is foundational to data processing operations and artificial intelligence (AI) applications.
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A modern data architecture acknowledges the idea that taking a one-size-fits-all approach to analytics eventually leads to compromises. It is not simply about integrating a data lake with a data warehouse, but rather about integrating a data lake, a data warehouse, and purpose-built stores, enabling unified governance and easy data movement.
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Data Architecture is foundational to an information-based operational environment. Without proper structure and efficiency in organization, data assets cannot be utilized to their full potential, which in turn harms bottom-line business value.
