data-streaming 
TechCrunch
FEBRUARY 8, 2023
The rise of streaming architectures — frameworks of software components built to ingest and process large volumes of data from multiple sources — is driving the demand for better reliability and performance. Engineering teams often encode data to improve app performance by using what are known as “message envelopes.”
TechCrunch
OCTOBER 3, 2022
In 2011, the Apache Software Foundation released Flink, a high-throughput, low-latency engine for streaming various data types. ” Temme acknowledges that there are other cloud services for Apache Flink, like Amazon Web Services’ (AWS) Kinesis Data Analytics and Aiven’s fully managed Apache Flink service.
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DevOps.com
JANUARY 27, 2023
Data streams are all the rage. Once a niche element of data engineering, streaming data is the new normal—more than 80% of Fortune 100 companies have adopted Apache Kafka, the most common streaming platform, and every major cloud provider (AWS, Google Cloud Platform and Microsoft Azure) has launched its own streaming service.
TechCrunch
JANUARY 26, 2021
Streaming data is not new. Vectorized was founded on the premise that the existing tools were too complex and not designed for today’s streaming requirements. Today the company released its first product, Redpanda , an open source tool designed to make it easier for developers to build streaming data applications.
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While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Traditional Business Intelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures.
Confluent
APRIL 30, 2024
Learn about the role of Confluent in streaming, processing, and governing sensitive healthcare data as part of a Single Patient View solution in healthcare.
Confluent
JUNE 8, 2023
ChatGPT and data streaming can work together for any company. Learn a basic framework for using GPT-4 and streaming to build a real-world production application.
Advertiser: ZoomInfo
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Advertiser: ZoomInfo
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Leading brands and local businesses alike are tapping into varied business and consumer data to power their products and meet consumers’ ever-evolving needs. But companies need to remember that a product can only be as good as the data that powers it. The criteria you should use to vet available data sources.
Speaker: Azmat Tanauli, Senior Director of Product Strategy at Birst
How much potential revenue is hidden in your data? In a recent Economist survey of 476 senior executives worldwide, 60% are already generating revenue from their data, and a whopping 83% have used data to make existing products or services more profitable.
Speaker: Javier RamÃrez, Senior AWS Developer Advocate, AWS
You have lots of data, and you are probably thinking of using the cloud to analyze it. But how will you move data into the cloud? How will you validate and prepare the data? What about streaming data? Can data scientists discover and use the data? Is your data secure? In which format?
Speaker: Sam Owens, Product Management Lead, Namely Platform
Sam and Jessica will walk through how they: Discovered the data and analytics needs of their users, including understanding what data sources they needed access to. To make things tougher, they needed something flexible, scalable and capable of serving different user types. Balanced competing priorities and managed expectations.
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As DevOps Value Stream Management (VSM) goes mainstream, large and small organizations increasingly recognize the need to apply data analytics to manage the end-to-end software delivery process more effectively – to deliver quality software faster and more predictably.
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