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Incremental refresh for Amazon Redshift materialized views on data lake tables

AWS Big Data

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it cost-effective to analyze your data using standard SQL and business intelligence tools. Customers use data lake tables to achieve cost effective storage and interoperability with other tools. Create an external schema.

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Accomplish Agile Business Intelligence & Analytics For Your Business

datapine

When encouraging these BI best practices what we are really doing is advocating for agile business intelligence and analytics. Therefore, we will walk you through this beginner’s guide on agile business intelligence and analytics to help you understand how they work and the methodology behind them.

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Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights. Choose Next to create your stack.

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Introducing a new unified data connection experience with Amazon SageMaker Lakehouse unified data connectivity

AWS Big Data

The product data is stored on Amazon Aurora PostgreSQL-Compatible Edition. Their existing business intelligence (BI) tool runs queries on Athena. Furthermore, they have a data pipeline to perform extract, transform, and load (ETL) jobs when moving data from the Aurora PostgreSQL database cluster to other data stores.

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Simplify data ingestion from Amazon S3 to Amazon Redshift using auto-copy

AWS Big Data

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze your data using standard SQL and your existing business intelligence (BI) tools. He was the CEO and co-founder of DataRow, which was acquired by Amazon in 2020.

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Perform upserts in a data lake using Amazon Athena and Apache Iceberg

AWS Big Data

Amazon Athena supports the MERGE command on Apache Iceberg tables, which allows you to perform inserts, updates, and deletes in your data lake at scale using familiar SQL statements that are compliant with ACID (Atomic, Consistent, Isolated, Durable). Navigate to the Athena console and choose Query editor.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

In this post, we show you how EUROGATE uses AWS services, including Amazon DataZone , to make data discoverable by data consumers across different business units so that they can innovate faster. See the YouTube playlist for some of the latest demos of Amazon DataZone and short descriptions of the capabilities available.

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