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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

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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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Choosing an open table format for your transactional data lake on AWS

AWS Big Data

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

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Simplify operational data processing in data lakes using AWS Glue and Apache Hudi

AWS Big Data

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. Of those tables, some are larger (such as in terms of record volume) than others, and some are updated more frequently than others.

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Exploring real-time streaming for generative AI Applications

AWS Big Data

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. FMs are multimodal; they work with different data types such as text, video, audio, and images.

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Estimating Scope 1 Carbon Footprint with Amazon Athena

AWS Big Data

As the only user-provided input is the amount spent on an activity, EIO LCA methods aren’t useful for modeling improved efficiency. 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.

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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. Simplify data management . 1: Multi-function analytics . 2: Open formats. Reproducibility for ML Ops.