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Achieve near real time operational analytics using Amazon Aurora PostgreSQL zero-ETL integration with Amazon Redshift

AWS Big Data

and zero-ETL support) as the source, and a Redshift data warehouse as the target. The integration replicates data from the source database into the target data warehouse. Additionally, you can choose the capacity, to limit the compute resources of the data warehouse. For this post, set this to 8 RPUs.

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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

There are two broad approaches to analyzing operational data for these use cases: Analyze the data in-place in the operational database (e.g. With Aurora zero-ETL integration with Amazon Redshift, the integration replicates data from the source database into the target data warehouse.

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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. Modern analytics is much wider than SQL-based data warehousing. Fault tolerance is built in. Any hardware failures are automatically replaced.

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What is business intelligence? Transforming data into business insights

CIO Business Intelligence

Improved employee satisfaction: Providing business users access to data without having to contact analysts or IT can reduce friction, increase productivity, and facilitate faster results. BI aims to deliver straightforward snapshots of the current state of affairs to business managers.

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Choosing an open table format for your transactional data lake on AWS

AWS Big Data

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale. Using column statistics , Iceberg offers efficient updates on tables that are sorted on a “key” column.

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Interview with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity

Corinium

Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. It definitely depends on the type of data, no one method is always better than the other.

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Unleashing the power of Presto: The Uber case study

IBM Big Data Hub

Presto was able to achieve this level of scalability by completely separating analytical compute from data storage. Presto is an open source distributed SQL query engine for data analytics and the data lakehouse, designed for running interactive analytic queries against datasets of all sizes, from gigabytes to petabytes.

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