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

AWS Big Data

In the subsequent post in our series, we will explore the architectural patterns in building streaming pipelines for real-time BI dashboards, contact center agent, ledger data, personalized real-time recommendation, log analytics, IoT data, Change Data Capture, and real-time marketing data.

Analytics 115
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Use Amazon OpenSearch Ingestion to migrate to Amazon OpenSearch Serverless

AWS Big Data

Migration of metadata such as security roles and dashboard objects will be covered in another subsequent post. Uncomment indices , include , index_name_regex , and add an index name or pattern that you want to migrate (for example, octank-iot-logs-2023.11.0* ).

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

Sources Data can be loaded from multiple sources, such as systems of record, data generated from applications, operational data stores, enterprise-wide reference data and metadata, data from vendors and partners, machine-generated data, social sources, and web sources. Let’s look at the components of the architecture in more detail.

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Visualize Amazon DynamoDB insights in Amazon QuickSight using the Amazon Athena DynamoDB connector and AWS Glue

AWS Big Data

These include internet-scale web and mobile applications, low-latency metadata stores, high-traffic retail websites, Internet of Things (IoT) and time series data, online gaming, and more. Table metadata, such as column names and data types, is stored using the AWS Glue Data Catalog. You don’t need to write any code.

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How to Manage Risk with Modern Data Architectures

Cloudera

Incorporate data from novel sources — social media feeds, alternative credit histories (utility and rental payments), geo-spatial systems, and IoT streams — into liquidity risk models. Financial institutions can use ML and AI to: Support liquidity monitoring and forecasting in real time.

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What is product lifecycle management? Organizing the development process

CIO Business Intelligence

Autodesk’s Upchain is a cloud-based product data management and product lifecycle management software that targets small and midsize companies with built-in workflow management and project dashboards. Oracle’s Fusion Cloud PLM platform leverages analytics, IoT, AI, and ML to deliver digital twin and digital thread capabilities.

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Build efficient, cross-Regional, I/O-intensive workloads with Dask on AWS

AWS Big Data

System administrators have access to the built-in Dask dashboard exposed via an Elastic Load Balancer. The OpenSearch Service domain stores metadata on the datasets connected at the Regions. A key feature of Lustre is that only the file system’s metadata is synced.