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

AWS Big Data

Within seconds of transactional data being written into supported AWS databases, zero-ETL seamlessly makes the data available in Amazon Redshift, removing the need to build and maintain complex data pipelines that perform extract, transform, and load (ETL) operations. For this post, set this to 8 RPUs. Choose Next.

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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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Exploring real-time streaming for generative AI Applications

AWS Big Data

Stream processing, however, can enable the chatbot to access real-time data and adapt to changes in availability and price, providing the best guidance to the customer and enhancing the customer experience. When the model finds an anomaly or abnormal metric value, it should immediately produce an alert and notify the operator.

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Architectural patterns for real-time analytics using Amazon Kinesis Data Streams, part 1

AWS Big Data

For high availability and durability, Kinesis Data Streams achieves high durability by synchronously replicating the streamed data across three Availability Zones in an AWS Region and gives you the option to retain data for up to 365 days. The raw data can be streamed to Amazon S3 for archiving.

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Financial Dashboard: Definition, Examples, and How-tos

FineReport

Financial Performance Dashboard The financial performance dashboard provides a comprehensive overview of key metrics related to your balance sheet, shedding light on the efficiency of your capital expenditure. The balance sheet plays a vital role in internal management, helping companies fine-tune their business strategies and prevent misuse.

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Now Available: Cloudera Data Science Workbench Release 1.4

Cloudera

With CDSW, organizations can research and experiment faster, deploy models easily and with confidence, as well as rely on the wider Cloudera platform to reduce the risks and costs of data science projects. track model metrics, performance, and any model artifacts the user specifies. Cloudera Data Science Workbench 1.4.x

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Enable Multi-AZ deployments for your Amazon Redshift data warehouse

AWS Big Data

Amazon Redshift is a fully managed, petabyte scale cloud data warehouse that enables you to analyze large datasets using standard SQL. Data warehouse workloads are increasingly being used with mission-critical analytics applications that require the highest levels of resilience and availability.