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Building end-to-end data lineage for one-time and complex queries using Amazon Athena, Amazon Redshift, Amazon Neptune and dbt

AWS Big Data

Complex queries, on the other hand, refer to large-scale data processing and in-depth analysis based on petabyte-level data warehouses in massive data scenarios. AWS Glue crawler crawls data lake information from Amazon S3, generating a Data Catalog to support dbt on Amazon Athena data modeling.

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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. Delta Lake doesn’t have a specific concept for incremental queries.

Data Lake 137
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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

It has far-reaching implications as to how such applications should be developed and by whom: ML applications are directly exposed to the constantly changing real world through data, whereas traditional software operates in a simplified, static, abstract world which is directly constructed by the developer. This approach is not novel.

IT 364
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How Gupshup built their multi-tenant messaging analytics platform on Amazon Redshift

AWS Big Data

About Redshift and some relevant features for the use case Amazon Redshift is a fully managed, petabyte-scale, massively parallel data warehouse that offers simple operations and high performance. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools.

Analytics 119
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Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes

AWS Big Data

The following examples are also available in the sample notebook in the aws-samples GitHub repo for quick experimentation. You can use either the AWS Glue Data Catalog (recommended) or a Hive catalog for Iceberg tables. In that case, we have to query the table with the snapshot-id corresponding to the deleted row.

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Build a multi-Region and highly resilient modern data architecture using AWS Glue and AWS Lake Formation

AWS Big Data

This post explains how to create a design that automatically backs up Amazon Simple Storage Service (Amazon S3), the AWS Glue Data Catalog, and Lake Formation permissions in different Regions and provides backup and restore options for disaster recovery. He specializes in migrating enterprise data warehouses to AWS Modern Data Architecture.

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Snowflake and Domino: Better Together

Domino Data Lab

Data Science works best with a high degree of data granularity when the data offers the closest possible representation of what happened during actual events – as in financial transactions, medical consultations or marketing campaign results. Domino Data Lab is the system-of-record for enterprise data science teams.