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

AWS Big Data

Now get ready as we embark on the second part of this series, where we focus on the AI applications with Kinesis Data Streams in three scenarios: real-time generative business intelligence (BI), real-time recommendation systems, and Internet of Things (IoT) data streaming and inferencing.

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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.

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Data Science News from Microsoft Ignite 2019

Data Science 101

Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Synapse allows one to use SQL to query petabytes of data, both relational and non-relational, with amazing speed. Visual Studio Online. Here they are in my order of importance (based upon my opinion). Azure Synapse.

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

AWS Big Data

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

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When Private Cloud is the Right Fit for Public Sector Missions

Cloudera

Through modern data architectures powered by CDP, including Cloudera-enabled data fabric, data lakehouse, and data mesh , DoD agencies can rapidly provision and manage innovative data engineering, data warehouse, and machine learning environments, with access to secured supply chain data stored in CDP Private Cloud.

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Data load made easy and secure in Amazon Redshift using Query Editor V2

AWS Big Data

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to analyze all your data efficiently and securely. Users such as data analysts, database developers, and data scientists use SQL to analyze their data in Amazon Redshift data warehouses.

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Transforming Big Data into Actionable Intelligence

Sisense

However, when investigating big data from the perspective of computer science research, we happily discover much clearer use of this cluster of confusing concepts. To best understand how to do this, let’s dig into the challenges of big data and look at a wave of emerging issues. displaying BI insights for human users).