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Power enterprise-grade Data Vaults with Amazon Redshift – Part 2

AWS Big Data

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

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Setting up and Getting Started with Cloudera’s New SQL AI Assistant

Cloudera

Supported AI models and services The SQL AI Assistant is not bundled with a specific LLM; instead it supports various LLMs and hosting services. The model can run locally, be hosted on CML infra or in the infrastructure of a trusted service provider. Log in to the Cloudera Data Warehouse service as DWAdmin.

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Orchestrate an end-to-end ETL pipeline using Amazon S3, AWS Glue, and Amazon Redshift Serverless with Amazon MWAA

AWS Big Data

As the queries finish running, an UNLOAD operation is invoked from the Redshift data warehouse to the S3 bucket in Account A. Cross-account access has been set up between S3 buckets in Account A with resources in Account B to be able to load and unload data. If the alternate backend contains the needed value, it is returned.

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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics, Part 3: Visualization and trend analysis using Amazon QuickSight

AWS Big Data

Data Firehose uses an AWS Lambda function to transform data and ingest the transformed records into an Amazon Simple Storage Service (Amazon S3) bucket. An AWS Glue crawler scans data on the S3 bucket and populates table metadata on the AWS Glue Data Catalog.

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The Top Three Entangled Trends in Data Architectures: Data Mesh, Data Fabric, and Hybrid Architectures

Cloudera

This team or domain expert will be responsible for the data produced by the team. The data itself is then treated as a product. The data product is not just the data itself, but a bunch of metadata that surrounds it — the simple stuff like schema is a given. Data fabric defined. What is a data mesh contract?

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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. These transactional data lakes combine features from both the data lake and the data warehouse. Data can be organized into three different zones, as shown in the following figure.

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Query your Apache Hive metastore with AWS Lake Formation permissions

AWS Big Data

Apache Hive is a SQL-based data warehouse system for processing highly distributed datasets on the Apache Hadoop platform. The Hive metastore is a repository of metadata about the SQL tables, such as database names, table names, schema, serialization and deserialization information, data location, and partition details of each table.