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Secure cloud fabric: Enhancing data management and AI development for the federal government

CIO Business Intelligence

In recent years, government agencies have increasingly turned to cloud computing to manage vast amounts of data and streamline operations. To address these challenges, agencies are turning to a secure cloud fabric that can ensure the confidentiality, integrity, and availability of their data in the cloud.

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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

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Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. We think of this concept as inside-out data movement.

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DS Smith sets a single-cloud agenda for sustainability

CIO Business Intelligence

Its digital transformation began with an application modernization phase, in which Dickson and her IT teams determined which applications should be hosted in the public cloud and which should remain on a private cloud. Having that data in the cloud and piping it into our data pipelines is a much more effective way to do that.”

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Your New Cloud for AI May Be Inside a Colo

CIO Business Intelligence

Many companies whose AI model training infrastructure is not proximal to their data lake incur steeper costs as the data sets grow larger and AI models become more complex. Companies such as Cyxtera, Digital Realty and Equinix, among others, offer hosting, managing and operations services for AI infrastructure.

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Enhance query performance using AWS Glue Data Catalog column-level statistics

AWS Big Data

Today, we’re making available a new capability of AWS Glue Data Catalog that allows generating column-level statistics for AWS Glue tables. These statistics are now integrated with the cost-based optimizers (CBO) of Amazon Athena and Amazon Redshift Spectrum , resulting in improved query performance and potential cost savings.

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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics, Part 3: Visualization and trend analysis using Amazon QuickSight

AWS Big Data

Analyzing historical patterns allows you to optimize performance, identify issues proactively, and improve planning. Typically, you have multiple accounts to manage and run resources for your data pipeline. In the navigation pane, choose Manage assets. On the Manage assets page, choose Datasets. Choose SHARE.

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