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Centralize near-real-time governance through alerts on Amazon Redshift data warehouses for sensitive queries

AWS Big Data

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud that delivers powerful and secure insights on all your data with the best price-performance. With Amazon Redshift, you can analyze your data to derive holistic insights about your business and your customers.

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Optimization Strategies for Iceberg Tables

Cloudera

Introduction Apache Iceberg has recently grown in popularity because it adds data warehouse-like capabilities to your data lake making it easier to analyze all your data — structured and unstructured. You can take advantage of a combination of the strategies provided and adapt them to your particular use cases.

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Dive deep into security management: The Data on EKS Platform

AWS Big Data

We show how Ranger integrates with Hadoop components like Apache Hive, Spark, Trino, Yarn, and HDFS, providing secure and efficient data management in a cloud environment. Join us as we navigate these advanced security strategies in the context of Kubernetes and cloud computing. In this case, it’s dep-demo-eks-cluster-ap-northeast-1.

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Manage your workloads better using Amazon Redshift Workload Management

AWS Big Data

With Amazon Redshift , you can run a complex mix of workloads on your data warehouse, such as frequent data loads running alongside business-critical dashboard queries and complex transformation jobs. We also see more and more data science and machine learning (ML) workloads. ExampleCorp has multiple Redshift clusters.

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Bringing More AI to Snowflake, the Data Cloud

DataRobot Blog

While this can be an excellent strategy for a future-oriented company, it can prove futile if you don’t maximize the value of your investment. According to Flexera 1 , 92% of enterprises have a multi-cloud strategy, while 80% have a hybrid cloud strategy. Learn more at DataRobot.com/Snowflake.

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Powering the future: The synergy of IBM and AWS partnership

IBM Big Data Hub

This collaboration recognizes that data and AI are inseparable allies in driving digital transformation. Data provides the raw materials for AI algorithms to learn and evolve, while AI extracts actionable insights from data that shape business strategies and customer experiences.

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Navigating Data Entities, BYOD, and Data Lakes in Microsoft Dynamics

Jet Global

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.