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The Five Use Cases in Data Observability: Mastering Data Production

DataKitchen

The Five Use Cases in Data Observability: Mastering Data Production (#3) Introduction Managing the production phase of data analytics is a daunting challenge. Overseeing multi-tool, multi-dataset, and multi-hop data processes ensures high-quality outputs.

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Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service is now available

AWS Big Data

Today, we are announcing the general availability of Amazon DocumentDB (with MongoDB compatibility) zero-ETL integration with Amazon OpenSearch Service. With Amazon OpenSearch Service, you can perform advanced search analytics, such as fuzzy search, synonym search, cross-collection search, and multilingual search, on Amazon DocumentDB data.

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Combine transactional, streaming, and third-party data on Amazon Redshift for financial services

AWS Big Data

Financial services customers are using data from different sources that originate at different frequencies, which includes real time, batch, and archived datasets. The challenge is to come up with a solution that can handle these disparate sources, varied frequencies, and low-latency consumption requirements.

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

AWS Big Data

Data is at the center of every application, process, and business decision. Customers across industries are becoming more data driven and looking to increase revenue, reduce cost, and optimize their business operations by implementing near real time analytics on transactional data, thereby enhancing agility.

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Announcing zero-ETL integrations with AWS Databases and Amazon Redshift

AWS Big Data

As customers become more data driven and use data as a source of competitive advantage, they want to easily run analytics on their data to better understand their core business drivers to grow sales, reduce costs, and optimize their businesses. ETL is the process data engineers use to combine data from different sources.

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Direct Lake and DirectQuery in the Age of Fabric

Paul Turley

Over 4,000 attendees saw a lot of demos showing how to effortlessly build a modern data platform with petabytes of data in One Lake, and then ask CoPilot to generate beautiful Power BI reports from semantic models that magically appear from data in a Fabric Lakehouse.

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Successfully conduct a proof of concept in Amazon Redshift

AWS Big Data

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. For a POC on Amazon Redshift, we recommend a three-phase process of discovery, implementation, and evaluation.

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