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

AWS Big Data

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. The company wanted the ability to continue processing operational data in the secondary Region in the rare event of primary Region failure.

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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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Open Data Lakehouse powered by Iceberg for all your Data Warehouse needs

Cloudera

In this blog, we will share with you in detail how Cloudera integrates core compute engines including Apache Hive and Apache Impala in Cloudera Data Warehouse with Iceberg. We will publish follow up blogs for other data services. Iceberg basics Iceberg is an open table format designed for large analytic workloads.

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Build and manage your modern data stack using dbt and AWS Glue through dbt-glue, the new “trusted” dbt adapter

AWS Big Data

We have seen a strong customer demand to expand its scope to cloud-based data lakes because data lakes are increasingly the enterprise solution for large-scale data initiatives due to their power and capabilities. Let’s say that this company is located in Europe and the data product must comply with the GDPR.

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Implement a serverless CDC process with Apache Iceberg using Amazon DynamoDB and Amazon Athena

AWS Big Data

Iceberg manages large collections of files as tables, and it supports modern analytical data lake operations such as record-level insert, update, delete, and time travel queries. Most businesses store their critical data in a data lake, where you can bring data from various sources to a centralized storage.

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Interact with Apache Iceberg tables using Amazon Athena and cross account fine-grained permissions using AWS Lake Formation

AWS Big Data

It makes sharing data across LoBs non-trivial. These organizations have adopted a federated model, with each LoB having the autonomy to make decisions on their data. They use the publisher/consumer model with a centralized governance layer that is used to enforce access controls. The Iceberg table keeps track of the snapshots.

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Estimating Scope 1 Carbon Footprint with Amazon Athena

AWS Big Data

The Economic Input-Output Life Cycle Assessment (EIO LCA) method is a spend-based method that combines expenditure data with monetary-based emission factors to estimate the emissions produced. The emission factors are published by the U.S. Environment Protection Agency (EPA) and other peer-reviewed academic and government sources.