Remove data admin how-to-show-list-or-describe-tables-in-amazon-redshift
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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

Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed orchestration service for Apache Airflow that you can use to set up and operate data pipelines in the cloud at scale. This approach allows the team to process the raw data extracted from Account A to Account B, which is dedicated for data handling tasks.

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Migrate from Google BigQuery to Amazon Redshift using AWS Glue and Custom Auto Loader Framework

AWS Big Data

Amazon Redshift is a widely used, fully managed, petabyte-scale cloud data warehouse. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytic workloads. This pre-built solution scales to load data in parallel using input parameters.

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Automate deployment of an Amazon QuickSight analysis connecting to an Amazon Redshift data warehouse with an AWS CloudFormation template

AWS Big Data

Amazon Redshift is the most widely used data warehouse in the cloud, best suited for analyzing exabytes of data and running complex analytical queries. Amazon QuickSight is a fast business analytics service to build visualizations, perform ad hoc analysis, and quickly get business insights from your data.

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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.

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Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT

AWS Big Data

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. With Amazon Redshift Serverless and Query Editor v2 , you can load and query large datasets in just a few clicks and pay only for what you use.

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How BMO improved data security with Amazon Redshift and AWS Lake Formation

AWS Big Data

As they continue to implement their Digital First strategy for speed, scale and the elimination of complexity, they are always seeking ways to innovate, modernize and also streamline data access control in the Cloud. BMO has accumulated sensitive financial data and needed to build an analytic environment that was secure and performant.

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Getting started guide for near-real time operational analytics using Amazon Aurora zero-ETL integration with Amazon Redshift

AWS Big Data

Amazon Aurora zero-ETL integration with Amazon Redshift was announced at AWS re:Invent 2022 and is now available in public preview for Amazon Aurora MySQL-Compatible Edition 3 (compatible with MySQL 8.0) It minimizes the work of building and managing custom ETL pipelines between Aurora and Amazon Redshift.