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Use Apache Iceberg in your data lake with Amazon S3, AWS Glue, and Snowflake

AWS Big Data

They understand that a one-size-fits-all approach no longer works, and recognize the value in adopting scalable, flexible tools and open data formats to support interoperability in a modern data architecture to accelerate the delivery of new solutions.

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Load data incrementally from transactional data lakes to data warehouses

AWS Big Data

Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Data lakes store all of an organization’s data, regardless of its format or structure.

Data Lake 109
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Estimating Scope 1 Carbon Footprint with Amazon Athena

AWS Big Data

The data architecture diagram below shows an example of how you could use AWS services to calculate and visualize an organization’s estimated carbon footprint. Customers have the flexibility to choose the services in each stage of the data pipeline based on their use case. usage_therms", "gasutilization"."usage_scf"

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Architectural patterns for real-time analytics using Amazon Kinesis Data Streams, part 1

AWS Big Data

Kinesis Data Streams has native integrations with other AWS services such as AWS Glue and Amazon EventBridge to build real-time streaming applications on AWS. Refer to Amazon Kinesis Data Streams integrations for additional details. The raw data can be streamed to Amazon S3 for archiving.

Analytics 109
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Exploring real-time streaming for generative AI Applications

AWS Big Data

Furthermore, data events are filtered, enriched, and transformed to a consumable format using a stream processor. The result is made available to the application by querying the latest snapshot. OpenSearch Service offers visualization capabilities powered by OpenSearch Dashboards and Kibana (1.5

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Build incremental data pipelines to load transactional data changes using AWS DMS, Delta 2.0, and Amazon EMR Serverless

AWS Big Data

Building data lakes from continuously changing transactional data of databases and keeping data lakes up to date is a complex task and can be an operational challenge. You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes.

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5 Reasons to Use Apache Iceberg on Cloudera Data Platform (CDP)

Cloudera

In fact, we recently announced the integration with our cloud ecosystem bringing the benefits of Iceberg to enterprises as they make their journey to the public cloud, and as they adopt more converged architectures like the Lakehouse. 1: Multi-function analytics . 2: Open formats. Financial regulation. Reproducibility for ML Ops.