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Architectural Patterns for real-time analytics using Amazon Kinesis Data Streams, Part 2: AI Applications

AWS Big Data

Welcome back to our exciting exploration of architectural patterns for real-time analytics with Amazon Kinesis Data Streams! Before we dive in, we recommend reviewing Architectural patterns for real-time analytics using Amazon Kinesis Data Streams, part 1 for the basic functionalities of Kinesis Data Streams.

IoT 63
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Build Spark Structured Streaming applications with the open source connector for Amazon Kinesis Data Streams

AWS Big Data

Apache Spark is a powerful big data engine used for large-scale data analytics. You can use Apache Spark to process streaming data from a variety of streaming sources, including Amazon Kinesis Data Streams for use cases like clickstream analysis, fraud detection, and more.

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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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Uplevel your data architecture with real- time streaming using Amazon Data Firehose and Snowflake

AWS Big Data

Today’s fast-paced world demands timely insights and decisions, which is driving the importance of streaming data. Streaming data refers to data that is continuously generated from a variety of sources. Before Snowpipe Streaming, AWS customers used Snowpipe for both use cases: file ingestion and rowset ingestion.

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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. Additionally, they need streaming architectures to handle growing trade volumes, market volatility, and regulatory demands. version cluster.

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

AWS Big Data

We’re living in the age of real-time data and insights, driven by low-latency data streaming applications. The volume of time-sensitive data produced is increasing rapidly, with different formats of data being introduced across new businesses and customer use cases.

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Exploring real-time streaming for generative AI Applications

AWS Big Data

FMs are multimodal; they work with different data types such as text, video, audio, and images. Large language models (LLMs) are a type of FM and are pre-trained on vast amounts of text data and typically have application uses such as text generation, intelligent chatbots, or summarization.