AWS Big Data Blog

Category: Amazon Kinesis

How Optus improves broadband and mobile customer experience using the Network Data Analytics platform on AWS

This is a guest blog post co-written by Rajagopal Mahendran, Development Manager at the Optus IT Innovation Team. Optus is part of The Singtel group, which operates in one of the world’s fastest growing and most dynamic regions, with a presence in 21 countries. Optus provides not only core telecom services, but also an extensive […]

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Use Grok patterns in AWS Glue to process streaming data into Amazon Elasticsearch Service

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. Recently, we launched AWS Glue custom connectors for Amazon OpenSearch Service, which provides the capability to ingest data into Amazon OpenSearch with just a few clicks. You can now use Amazon OpenSearch as a data store for your extract, transform, […]

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Enrich your data stream asynchronously using Amazon Kinesis Data Analytics for Apache Flink

Streaming data into or out of a data system must be fast. One of the most expensive pieces of any streaming system is the I/O of the system: reading from the streaming layer using Apache Kafka or Amazon Kinesis, reading a file, writing to an Amazon Simple Storage Service (Amazon S3) data lake, or communicating […]

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How Isentia improves customer experience by modernizing their real-time media monitoring and intelligence platform with Amazon Kinesis Data Analytics for Apache Flink

This is a blog post co-written by Karl Platz at Isentia. In their own words, “Isentia is the leading media monitoring, intelligence and insights solution provider in Asia Pacific, helping top-performing communication teams make sense of the world’s conversations in real-time.” Isentia is a publicly listed (ASX:ISD) media monitoring and intelligence company that provides software […]

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Build seamless data streaming pipelines with Amazon Kinesis Data Streams and Amazon Kinesis Data Firehose for Amazon DynamoDB tables

The global wearables market grew 35.1% year over year during the third quarter of 2020, with total shipments reaching 125 million units according to new data from the International Data Corporation (IDC) Worldwide Quarterly Wearable Device Tracker. The surge was driven by seasonality, new product launches, and the health concerns during the global pandemic. Given […]

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Build a real-time streaming application using Apache Flink Python API with Amazon Kinesis Data Analytics

Amazon Kinesis Data Analytics is now expanding its Apache Flink offering by adding support for Python. This is exciting news for many of our customers who use Python as their primary language for application development. This new feature enables developers to build Apache Flink applications in Python using serverless Kinesis Data Analytics. With Kinesis Data […]

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Build a serverless tracking pixel solution in AWS

Let’s describe the typical use case where a tracking pixel solution, also known as a web beacon, might help you: Analyzing web traffic is critical to understanding user behavior in order to improve their experience. Let’s think about a company—Example Company Hotels—that embeds a piece of HTML into a high-traffic, third-party website (example.HighTrafficWebsite.com) to have […]

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The following diagram shows our solution architecture.

Effective data lakes using AWS Lake Formation, Part 2: Creating a governed table for streaming data sources

We announced the preview of AWS Lake Formation transactions, row-level security, and acceleration at AWS re:Invent 2020. In Part 1 of this series, we explained how to set up a governed table and add objects to it. In this post, we expand on this example, and demonstrate how to ingest streaming data into governed tables using Lake Formation transactions. […]

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Build a data lake using Amazon Kinesis Data Streams for Amazon DynamoDB and Apache Hudi

Amazon DynamoDB helps you capture high-velocity data such as clickstream data to form customized user profiles and online order transaction data to develop customer order fulfillment applications, improve customer satisfaction, and get insights into sales revenue to create a promotional offer for the customer. It’s essential to store these data points in a centralized data […]

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The following diagram illustrates the architecture of this intermediate pipeline to generate training data.

Retaining data streams up to one year with Amazon Kinesis Data Streams

Streaming data is used extensively for use cases like sharing data between applications, streaming ETL (extract, transform, and load), real-time analytics, processing data from internet of things (IoT) devices, application monitoring, fraud detection, live leaderboards, and more. Typically, data streams are stored for short durations of time before being loaded into a permanent data store […]

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