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

AWS Big Data

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 116
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Exploring real-time streaming for generative AI Applications

AWS Big Data

This dynamic integration of streaming data enables generative AI applications to respond promptly to changing conditions, improving their adaptability and overall performance in various tasks. To better understand this, imagine a chatbot that helps travelers book their travel.

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Here’s Why Data Conferences Are Important: What You Need To Know

Smart Data Collective

You could listen to podcasts and read books — and you should be doing just that! But data conferences arguably offer some of the best opportunities to experience the most forward-thinking personalities and cutting-edge ideas in technology and data science fields. Book recommendations? Am I looking for a mentor?

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Data Observability and Monitoring with DataOps

DataKitchen

That’s a fair point, and it places emphasis on what is most important – what best practices should data teams employ to apply observability to data analytics. We see data observability as a component of DataOps. In our definition of data observability, we put the focus on the important goal of eliminating data errors.

Testing 214
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How Amazon optimized its high-volume financial reconciliation process with Amazon EMR for higher scalability and performance

AWS Big Data

Amazon EMR stands as a dynamic force in the cloud, delivering unmatched capabilities for organizations seeking robust big data solutions. Its seamless integration, powerful features, and adaptability make it an indispensable tool for navigating the complexities of data analytics and ML on AWS.

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Become a Financial Storyteller

Jet Global

Microsoft Excel offers flexibility, but it’s missing so many of the elements required to assemble data quickly and easily for powerful (and accurate) financial narratives. The reports created within static spreadsheets are based on a snapshot of reality, taken the moment the data was exported from ERP.

Finance 52
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Top Financial Reporting Challenges and How to Solve Them

Jet Global

There is yet another problem with manual processes: the resulting reports only reflect a snapshot in time. As soon as you export data from your ERP software or other business systems, it’s obsolete.