Remove tag information-management
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Introducing enhanced functionality for worker configuration management in Amazon MSK Connect

AWS Big Data

Amazon MSK Connect is a fully managed service for Apache Kafka Connect. MSK Connect now supports the ability to delete MSK Connect worker configurations, tag resources, and manage worker configurations and custom plugins using AWS CloudFormation. Resource tags MSK Connect now also has support for resource tags.

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Multicloud data lake analytics with Amazon Athena

AWS Big Data

With a unified query interface, you can avoid the complexity of managing multiple query tools and gain a holistic view of your data assets regardless of where the data assets reside. You can consolidate your analytics workflows, reducing the need for extensive tooling and infrastructure management.

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Use AWS Glue ETL to perform merge, partition evolution, and schema evolution on Apache Iceberg

AWS Big Data

Apache Iceberg manages these schema changes in a backward-compatible way through its innovative metadata table evolution architecture. Due to the security requirements of different organizations, they need to manage fine-grained access control for the analysts through Lake Formation. The changes can contain schema updates as well.

Snapshot 110
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DIY cloud cost management: The strategic case for building your own tools

CIO Business Intelligence

Cloud cost management remains a critical CIO priority. For CIOs who may need to customize their cloud cost information streams or manage a complex cloud estate, do-it-yourself cloud cost management may be the way to go.

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Are You Content with Your Organization’s Content Strategy?

Rocket-Powered Data Science

In “information retrieval” language, we would say that we have high RECALL, but low PRECISION. The key to success is to start enhancing and augmenting content management systems (CMS) with additional features: semantic content and context. This is accomplished through tags, annotations, and metadata (TAM).

Strategy 266
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Measure performance of AWS Glue Data Quality for ETL pipelines

AWS Big Data

As part of the results, we show how AWS Glue Data Quality provides information about the runtime of extract, transform, and load (ETL) jobs, the resources measured in terms of data processing units (DPUs), and how you can track the cost of running AWS Glue Data Quality for ETL pipelines by defining custom cost reporting in AWS Cost Explorer.

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Automated data governance with AWS Glue Data Quality, sensitive data detection, and AWS Lake Formation

AWS Big Data

Data confidentiality refers to the protection and control of sensitive and private information to prevent unauthorized access, especially when dealing with personally identifiable information (PII). Currently, these requirements are hard-coded and managed manually for each set of users.