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Posted to commits@beam.apache.org by gi...@apache.org on 2022/08/17 22:17:12 UTC

[beam] branch asf-site updated: Publishing website 2022/08/17 22:17:06 at commit 72d46e2

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The following commit(s) were added to refs/heads/asf-site by this push:
     new b9fa788f2e4 Publishing website 2022/08/17 22:17:06 at commit 72d46e2
b9fa788f2e4 is described below

commit b9fa788f2e462a329f3030a3e09a6741ab1140c9
Author: jenkins <bu...@apache.org>
AuthorDate: Wed Aug 17 22:17:07 2022 +0000

    Publishing website 2022/08/17 22:17:06 at commit 72d46e2
---
 website/generated-content/case-studies/index.html  |   3 +-
 website/generated-content/case-studies/index.xml   | 147 ++++++++++++++++++++-
 .../case-studies/intuit/index.html                 |  29 ++++
 .../images/case-study/intuit/intuit-quote.png      | Bin 0 -> 4190 bytes
 .../intuit/intuit_stream_processing_pipeline.png   | Bin 0 -> 65130 bytes
 .../images/case-study/intuit/nick_hwang.png        | Bin 0 -> 10414 bytes
 .../intuit/stream_processing_tech_stack.png        | Bin 0 -> 198943 bytes
 .../images/logos/powered-by/intuit.png             | Bin 0 -> 3801 bytes
 website/generated-content/index.html               |   3 +-
 website/generated-content/sitemap.xml              |   2 +-
 10 files changed, 180 insertions(+), 4 deletions(-)

diff --git a/website/generated-content/case-studies/index.html b/website/generated-content/case-studies/index.html
index de415987ce8..9b9fc7001cd 100644
--- a/website/generated-content/case-studies/index.html
+++ b/website/generated-content/case-studies/index.html
@@ -20,7 +20,8 @@ function addPlaceholder(){$('input:text').attr('placeholder',"What are you looki
 function endSearch(){var search=document.querySelector(".searchBar");search.classList.add("disappear");var icons=document.querySelector("#iconsBar");icons.classList.remove("disappear");}
 function blockScroll(){$("body").toggleClass("fixedPosition");}
 function openMenu(){addPlaceholder();blockScroll();}</script><div class="clearfix container-main-content"><nav class="page-nav clearfix" data-offset-top=90 data-offset-bottom=500><nav id=TableOfContents></nav></nav><div class="body__contained body__section-no-nav--wide case-study-page"><div class=blog-content><h1>Case Studies</h1><p class=case-study-about>Apache Beam powers many of today’s leading projects, industry-specific use cases, and
-startups.</p><div class=case-study-list><div class=case-study-card><div class=case-study-card-img><img src=/images/logos/powered-by/lyft.png></i></div><h3 class=case-study-card-title>Real-time ML with Beam at Lyft</h3><p class=case-study-card-description>Lyft Marketplace team aims to improve our business efficiency by being nimble to real-world dynamics. Apache Beam has enabled us to meet the goal of having a robust and scalable ML infrastructure for improving model accuracy with feature [...]
+startups.</p><div class=case-study-list><div class=case-study-card><div class=case-study-card-img><img src=/images/logos/powered-by/intuit.png></i></div><h3 class=case-study-card-title>Powering Streaming and Real-time ML at Intuit</h3><p class=case-study-card-description>We feel that the runner agnosticism of Apache Beam affords flexibility and future-proofs our Stream Processing Platform as new runtimes are developed. Apache Beam enabled the democratization of stream processing at Intui [...]
+<img src=/images/arrow-right.svg alt="Go to the case study"></a></div><div class=case-study-card><div class=case-study-card-img><img src=/images/logos/powered-by/lyft.png></i></div><h3 class=case-study-card-title>Real-time ML with Beam at Lyft</h3><p class=case-study-card-description>Lyft Marketplace team aims to improve our business efficiency by being nimble to real-world dynamics. Apache Beam has enabled us to meet the goal of having a robust and scalable ML infrastructure for improvi [...]
 <img src=/images/arrow-right.svg alt="Go to the case study"></a></div><div class=case-study-card><div class=case-study-card-img><img src=/images/logos/powered-by/paloalto.png></i></div><h3 class=case-study-card-title>Real-time Event Stream Processing at Scale for Palo Alto Networks</h3><p class=case-study-card-description>Palo Alto Networks is a global cybersecurity leader that deals with processing hundreds of billions of security events per day in real-time, which is on the high end of [...]
 <img src=/images/arrow-right.svg alt="Go to the case study"></a></div><div class=case-study-card><div class=case-study-card-img><img src=/images/logos/powered-by/hop.svg></i></div><h3 class=case-study-card-title>Visual Apache Beam Pipeline Design and Orchestration with Apache Hop</h3><p class=case-study-card-description>Apache Hop is an open source data orchestration and engineering platform that extends Apache Beam with visual pipeline lifecycle management. Neo4j’s Chief Solution Archit [...]
 <img src=/images/arrow-right.svg alt="Go to the case study"></a></div><div class=case-study-card><div class=case-study-card-img><img src=/images/logos/powered-by/seznam.png></i></div><h3 class=case-study-card-title>Scalability and Cost Optimization for Search Engine's Workloads</h3><p class=case-study-card-description>Dive into the Czech search engine’s experience of scaling the on-premises infrastructure to learn more about the benefits of byte-based data shuffling and the use cases whe [...]
diff --git a/website/generated-content/case-studies/index.xml b/website/generated-content/case-studies/index.xml
index c6f0992d164..66010298193 100644
--- a/website/generated-content/case-studies/index.xml
+++ b/website/generated-content/case-studies/index.xml
@@ -1,4 +1,149 @@
-<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Apache Beam – Case Studies</title><link>/case-studies/</link><description>Recent content in Case Studies on Apache Beam</description><generator>Hugo -- gohugo.io</generator><atom:link href="/case-studies/index.xml" rel="self" type="application/rss+xml"/><item><title>Case-Studies: Real-time ML with Beam at Lyft</title><link>/case-studies/lyft/</link><pubDate>Fri, 17 Jun 2022 00:12:00 +0000</pubDate><guid>/case-stu [...]
+<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Apache Beam – Case Studies</title><link>/case-studies/</link><description>Recent content in Case Studies on Apache Beam</description><generator>Hugo -- gohugo.io</generator><atom:link href="/case-studies/index.xml" rel="self" type="application/rss+xml"/><item><title>Case-Studies: Powering Streaming and Real-time ML at Intuit</title><link>/case-studies/intuit/</link><pubDate>Tue, 16 Aug 2022 00:12:00 +0000</pubDat [...]
+&lt;!--
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+http://www.apache.org/licenses/LICENSE-2.0
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+-->
+&lt;div class="case-study-opinion">
+&lt;div class="case-study-opinion-img">
+&lt;img src="/images/logos/powered-by/intuit.png"/>
+&lt;/div>
+&lt;blockquote class="case-study-quote-block">
+&lt;p class="case-study-quote-text">
+“We feel that the runner agnosticism of Apache Beam affords flexibility and future-proofs our Stream Processing Platform as new runtimes are developed. Apache Beam enabled the democratization of stream processing at Intuit and the migration of many batch jobs to streaming applications.”
+&lt;/p>
+&lt;div class="case-study-quote-author">
+&lt;div class="case-study-quote-author-img">
+&lt;img src="/images/case-study/intuit/nick_hwang.png">
+&lt;/div>
+&lt;div class="case-study-quote-author-info">
+&lt;div class="case-study-quote-author-name">
+Nick Hwang
+&lt;/div>
+&lt;div class="case-study-quote-author-position">
+Engineering Manager, Stream Processing Platform @ Intuit
+&lt;/div>
+&lt;/div>
+&lt;/div>
+&lt;/blockquote>
+&lt;/div>
+&lt;div class="case-study-post">
+&lt;h1 id="powering-streaming-and-real-time-ml-at-intuit">Powering Streaming and Real-time ML at Intuit&lt;/h1>
+&lt;h2 id="background">Background&lt;/h2>
+&lt;p>&lt;a href="https://www.intuit.com/">Intuit®&lt;/a> is a global technology platform that provides a range of financial and marketing automation solutions, including &lt;a href="https://turbotax.intuit.com/">TurboTax&lt;/a>, &lt;a href="https://quickbooks.intuit.com/">QuickBooks&lt;/a>, &lt;a href="https://mint.intuit.com/">Mint&lt;/a>, &lt;a href="https://www.creditkarma.com/">Credit Karma&lt;/a>, and &lt;a href="https://mailchimp.com/">Mailchimp&lt;/a>, on its mission to power pro [...]
+&lt;p>Intuit developed an internal self-service Stream Processing Platform that leverages Apache Beam to accelerate time-to-market for real-time applications.&lt;/p>
+&lt;p>Nick Hwang, an Engineering Manager on the Intuit Data Infrastructure team, shared the story of how Apache Beam was used to build Intuit’s self-service Stream Processing Platform and provided a simple, intuitive way for developers to author, deploy, and manage streaming pipelines.&lt;/p>
+&lt;h2 id="self-service-stream-processing">Self-service Stream Processing&lt;/h2>
+&lt;p>When looking for AI and data-driven solutions to enhance their portfolio of financial management products, the Intuit Data Infrastructure and product teams saw an immense need for a self-service data processing platform. Their data engineers and developers needed a “paved road” to develop real-time applications while abstracting the low-level operational and infrastructure management details.&lt;/p>
+&lt;p>In 2019, Intuit’s Data Infrastructure team started designing their Stream Processing Platform with a mission to enable developers to focus on business logic, while the platform handles all the operational and infrastructure management details on their behalf.&lt;/p>
+&lt;blockquote class="case-study-quote-block case-study-quote-wrapped">
+&lt;p class="case-study-quote-text">
+The promise of our platform is that you don't have to worry about the deployment at first. You just update your code artifact, add the transformations that you want, point the pipeline to your sources and sinks, and we'll take care of the rest. You click a button and the platform will deploy your jobs for you.
+&lt;/p>
+&lt;div class="case-study-quote-author">
+&lt;div class="case-study-quote-author-img">
+&lt;img src="/images/case-study/intuit/nick_hwang.png">
+&lt;/div>
+&lt;div class="case-study-quote-author-info">
+&lt;div class="case-study-quote-author-name">
+Nick Hwang
+&lt;/div>
+&lt;div class="case-study-quote-author-position">
+Engineering Manager, Stream Processing Platform @ Intuit
+&lt;/div>
+&lt;/div>
+&lt;/div>
+&lt;/blockquote>
+&lt;p>Apache Beam was selected as Intuit’s Stream Processing Platform’s core data processing technology due to its flexibility to choose from a variety of &lt;a href="/documentation/sdks/java/">programming languages&lt;/a> and &lt;a href="/documentation/runners/capability-matrix/">execution engines&lt;/a>. Apache Beam’s portability and ease of adoption provided the necessary “jump-start” for the launch of the initial platform version, which used &lt;a href="https://samza.apache.org/">Apa [...]
+&lt;blockquote class="case-study-quote-block case-study-quote-wrapped">
+&lt;p class="case-study-quote-text">
+The primary reason why we chose Apache Beam was runner agnosticism. Our platform was a long-term investment and we wanted to be prepared for whatever may be coming eventually.
+&lt;/p>
+&lt;div class="case-study-quote-author">
+&lt;div class="case-study-quote-author-img">
+&lt;img src="/images/case-study/intuit/nick_hwang.png">
+&lt;/div>
+&lt;div class="case-study-quote-author-info">
+&lt;div class="case-study-quote-author-name">
+Nick Hwang
+&lt;/div>
+&lt;div class="case-study-quote-author-position">
+Engineering Manager, Stream Processing Platform @ Intuit
+&lt;/div>
+&lt;/div>
+&lt;/div>
+&lt;/blockquote>
+&lt;p>In January 2020, the first version of Intuit’s Stream Processing Platform &lt;a href="https://www.ververica.com/blog/how-intuit-built-a-self-serve-stream-processing-platform-with-flink">was launched&lt;/a>. Soon enough, the Apache Beam abstraction of the execution engines proved its benefits, allowing Intuit to seamlessly switch its data processing infrastructure from Apache Samza to &lt;a href="https://flink.apache.org/">Apache Flink&lt;/a> without causing any user pain points or  [...]
+&lt;blockquote class="case-study-quote-block case-study-quote-wrapped">
+&lt;p class="case-study-quote-text">
+When we decided to pivot from Apache Samza to Apache Flink, we had a couple dozen use cases and pipelines running in production, but none of the users had to change their code. The benefits of Apache Beam really showcased themselves in that case.
+&lt;/p>
+&lt;div class="case-study-quote-author">
+&lt;div class="case-study-quote-author-img">
+&lt;img src="/images/case-study/intuit/nick_hwang.png">
+&lt;/div>
+&lt;div class="case-study-quote-author-info">
+&lt;div class="case-study-quote-author-name">
+Nick Hwang
+&lt;/div>
+&lt;div class="case-study-quote-author-position">
+Engineering Manager, Stream Processing Platform @ Intuit
+&lt;/div>
+&lt;/div>
+&lt;/div>
+&lt;/blockquote>
+&lt;p>The Intuit Stream Processing Platform team benefitted from Apache Beam’s extensibility, which allowed them to easily wrap Apache Beam with a custom SDK layer for better interoperability with their specific Kafka installation. They paired the SDK with a graphic user interface to provide a visual way to design, manage, deploy, monitor, and debug data processing pipelines, as well as &lt;a href="https://argoproj.github.io/">Argo Workflows&lt;/a> to facilitate deployment on Kubernetes. [...]
+&lt;p>The Stream Processing Platform provides developers with a full stack environment to visually design streaming pipelines; test, provision, and promote them to production; and monitor the pipelines in production. Developers create Apache Beam pipelines with the Beam Java SDK at the Stream Processing Platform’s Application Layer (see layers below). Intuit’s graphic user interface (the UX Layer) enables visual configuration of sinks and sources, compute resource scaling, pipeline lifec [...]
+&lt;p>With the promise of an out-of-the-box solution, Intuit’s Stream Processing Platform has been designed to allow reusable templated implementations to accelerate the development of common use cases, while still providing the ability to customize for standalone applications. For instance, Intuit created its own DSL interface to provide custom configurations for simple transformations of the clickstream topics.&lt;/p>
+&lt;div class="post-scheme">
+&lt;img src="/images/case-study/intuit/stream_processing_tech_stack.png" alt="Intuit Stream Processing Platform’s Tech Stack">
+&lt;span>Intuit Stream Processing Platform’s Tech Stack&lt;/span>
+&lt;/div>
+&lt;p>The platform empowered much easier adoption of stream processing, providing self-service capabilities for Intuit’s data engineers and developers.&lt;/p>
+&lt;blockquote class="case-study-quote-block case-study-quote-wrapped">
+&lt;p class="case-study-quote-text">
+The whole idea of our platform is to minimize the barrier to entry to get your real-time application up and running. Like, “I just want to run this SQL query on a Kafka topic and write it to some sink, tell me how to do that in a day and not two months.
+&lt;/p>
+&lt;div class="case-study-quote-author">
+&lt;div class="case-study-quote-author-img">
+&lt;img src="/images/case-study/intuit/nick_hwang.png">
+&lt;/div>
+&lt;div class="case-study-quote-author-info">
+&lt;div class="case-study-quote-author-name">
+Nick Hwang
+&lt;/div>
+&lt;div class="case-study-quote-author-position">
+Engineering Manager, Stream Processing Platform @ Intuit
+&lt;/div>
+&lt;/div>
+&lt;/div>
+&lt;/blockquote>
+&lt;h2 id="powering-real-time-data">Powering Real-time Data&lt;/h2>
+&lt;p>Apache Beam-powered unified &lt;a href="https://www.gartner.com/en/information-technology/glossary/clickstream-analysis">clickstream&lt;/a> processing is the most impactful of Intuit’s use cases. The Apache Beam streaming pipeline consumes, aggregates, and processes raw clickstream events, such as website visits, from Kafka across the large portfolio of Intuit’s products. The clickstream pipeline enriches the data with geolocation along with other new features, sessionizes and stan [...]
+&lt;div class="post-scheme">
+&lt;img src="/images/case-study/intuit/intuit_stream_processing_pipeline.png" alt="Intuit Stream Processing Platform’s Pipeline Topology">
+&lt;span>Intuit Stream Processing Platform’s Pipeline Topology&lt;/span>
+&lt;/div>
+&lt;p>Another front-and-center Apache Beam use case from Intuit’s business perspective is the feature store ingestion platform that enables new AI and ML-powered customer experiences. Several Apache Beam pipelines take in real-time features generated by other Apache Beam pipelines on the platform from Kafka and write them to the Intuit feature store for ML model training and inference. Pipelines generating real-time features can also use a capability offered by the platform to &amp;ldquo [...]
+&lt;h2 id="results">Results&lt;/h2>
+&lt;p>Since Intuit Stream Processing Platform’s launch, the number of Apache Beam-powered streaming pipelines has been growing 2x per year and as of July’22 reached over 160 active production pipelines running on 710 nodes across 6 different Kubernetes clusters. The Apache Beam pipelines handle ~17.3 billion events and 82 TB of data, processing 800,000 transactions per second at peak seasons.&lt;/p>
+&lt;p>Apache Beam and its abstraction of the execution engines allowed Intuit to seamlessly switch their primary runner without rewriting the code to a new execution environment runner. It also provided confidence by future-proofing the Intuit Stream Processing Platform for flexibility as new execution runtimes keep evolving. Apache Beam helped lower the entry barrier, democratize stream processing across Intuit’s development teams, and ensure fast onboarding for engineers without prior  [...]
+&lt;p>With Apache Beam, Intuit accelerated the development and launch of production-grade streaming data pipelines 3x, from 3 months to just 1 month. The time to design pipelines for preproduction shrank to just 10 days. Migration from batch jobs to Apache Beam streaming pipelines resulted in a 5x memory and compute cost optimization. Intuit continues developing Apache Beam streaming pipelines for new use cases, 150 more pipelines are in preproduction and coming to production soon.&lt;/p>
+&lt;div class="case-study-feedback" id="case-study-feedback">
+&lt;p class="case-study-feedback-title">Was this information useful?&lt;/p>
+&lt;div>
+&lt;button class="btn case-study-feedback-btn" onclick="sendCaseStudyFeedback(true, 'Intuit')">Yes&lt;/button>
+&lt;button class="btn case-study-feedback-btn" onclick="sendCaseStudyFeedback(false, 'Intuit')">No&lt;/button>
+&lt;/div>
+&lt;/div>
+&lt;/div>
+&lt;div class="clear-nav">&lt;/div></description></item><item><title>Case-Studies: Real-time ML with Beam at Lyft</title><link>/case-studies/lyft/</link><pubDate>Fri, 17 Jun 2022 00:12:00 +0000</pubDate><guid>/case-studies/lyft/</guid><description>
 &lt;!--
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
diff --git a/website/generated-content/case-studies/intuit/index.html b/website/generated-content/case-studies/intuit/index.html
new file mode 100644
index 00000000000..25d30cd0c2e
--- /dev/null
+++ b/website/generated-content/case-studies/intuit/index.html
@@ -0,0 +1,29 @@
+<!doctype html><html lang=en class=no-js><head><meta charset=utf-8><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=viewport content="width=device-width,initial-scale=1"><title>Powering Streaming and Real-time ML at Intuit</title><meta name=description content="Apache Beam is an open source, unified model and set of language-specific SDKs for defining and executing data processing workflows, and also data ingestion and integration flows, supporting Enterprise Integration Pat [...]
+<a class=navbar-link href=/get-started/beam-overview/>Get Started</a>
+<a class=navbar-link href=/documentation/>Documentation</a>
+<button type=button class="navbar-toggle menu-open" aria-expanded=false aria-controls=navbar onclick=openMenu()>
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+&nbsp;Apache
+<span class=arrow-icon><svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="none" viewBox="0 0 20 20"><circle cx="10" cy="10" r="10" fill="#ff6d00"/><path stroke="#fff" stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M8.535 5.28l4.573 4.818-4.573 4.403"/></svg></span></a><ul class="dropdown-menu dropdown-menu-right"><li><a target=_blank href=http://www.apache.org/>ASF Homepage</a></li><li><a target=_blank href=http://www.apache.org/licenses/>License</a> [...]
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+<span><svg xmlns="http://www.w3.org/2000/svg" width="12" height="11" fill="none" viewBox="0 0 12 11"><path stroke="#ff6d00" stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M10.666 4.535 5.847 9.108 1.444 4.535"/></svg></span></a><ul class=dropdown-menu><li><a class=navbar-dropdown-menu-link href=/documentation/>General</a></li><li><a class=navbar-dropdown-menu-link href=/documentation/sdks/java/>Languages</a></li><li><a class=navbar-dropdown-menu-link href=/documentati [...]
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+<a class=navbar-link href=/case-studies/>Case Studies</a></div><div id=iconsBar><a type=button onclick=showSearch()><svg xmlns="http://www.w3.org/2000/svg" width="25" height="24" fill="none" viewBox="0 0 25 24"><path stroke="#ff6d00" stroke-linecap="round" stroke-linejoin="round" stroke-width="2.75" d="M10.191 17c3.866.0 7-3.134 7-7s-3.134-7-7-7-7 3.134-7 7 3.134 7 7 7zM21.191 21l-6-6"/></svg></a><a target=_blank href=https://github.com/apache/beam/edit/master/website/www/site/content/en [...]
+&nbsp;Apache
+<span class=arrow-icon><svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="none" viewBox="0 0 20 20"><circle cx="10" cy="10" r="10" fill="#ff6d00"/><path stroke="#fff" stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M8.535 5.28l4.573 4.818-4.573 4.403"/></svg></span></a><ul class=dropdown-menu><li><a class=navbar-dropdown-menu-link target=_blank href=http://www.apache.org/>ASF Homepage</a></li><li><a class=navbar-dropdown-menu-link target=_blank href=h [...]
+function addPlaceholder(){$('input:text').attr('placeholder',"What are you looking for?");}
+function endSearch(){var search=document.querySelector(".searchBar");search.classList.add("disappear");var icons=document.querySelector("#iconsBar");icons.classList.remove("disappear");}
+function blockScroll(){$("body").toggleClass("fixedPosition");}
+function openMenu(){addPlaceholder();blockScroll();}</script><div class="clearfix container-main-content"><nav class="page-nav clearfix" data-offset-top=90 data-offset-bottom=500><nav id=TableOfContents><ul><li><a href=#background>Background</a></li><li><a href=#self-service-stream-processing>Self-service Stream Processing</a></li><li><a href=#powering-real-time-data>Powering Real-time Data</a></li><li><a href=#results>Results</a></li></ul></nav></nav><div class=case-study-page><article  [...]
+<span>Intuit Stream Processing Platform’s Tech Stack</span></div><p>The platform empowered much easier adoption of stream processing, providing self-service capabilities for Intuit’s data engineers and developers.</p><blockquote class="case-study-quote-block case-study-quote-wrapped"><p class=case-study-quote-text>The whole idea of our platform is to minimize the barrier to entry to get your real-time application up and running. Like, “I just want to run this SQL query on a Kafka topic a [...]
+<span>Intuit Stream Processing Platform’s Pipeline Topology</span></div><p>Another front-and-center Apache Beam use case from Intuit’s business perspective is the feature store ingestion platform that enables new AI and ML-powered customer experiences. Several Apache Beam pipelines take in real-time features generated by other Apache Beam pipelines on the platform from Kafka and write them to the Intuit feature store for ML model training and inference. Pipelines generating real-time fea [...]
+<button class="btn case-study-feedback-btn" onclick="sendCaseStudyFeedback(false,'Intuit')">No</button></div></div></div><div class=clear-nav></div></div></div></div></article></div></div><footer class=footer><div class=footer__contained><div class=footer__cols><div class="footer__cols__col footer__cols__col__logos"><div class=footer__cols__col__logo><img src=/images/beam_logo_circle.svg class=footer__logo alt="Beam logo"></div><div class=footer__cols__col__logo><img src=/images/apache_l [...]
+<a href=http://www.apache.org>The Apache Software Foundation</a>
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-You can try the Apache Beam examples at <a href=https://play.beam.apache.org/>Beam Playground (Beta)</a>.</p><br><br><a class=playground__mobile href=https://play.beam.apache.org/><img src=images/playground.png alt="beam playground"></a><div class=playground-iframe-wrapper-no-scroll><iframe src="https://play.beam.apache.org/embedded?editable=1&example=SDK_JAVA/PRECOMPILED_OBJECT_TYPE_EXAMPLE/MinimalWordCount" width=100% height=700px class="code-snippet playground" allow=clipboard-write>< [...]
+You can try the Apache Beam examples at <a href=https://play.beam.apache.org/>Beam Playground (Beta)</a>.</p><br><br><a class=playground__mobile href=https://play.beam.apache.org/><img src=images/playground.png alt="beam playground"></a><div class=playground-iframe-wrapper-no-scroll><iframe src="https://play.beam.apache.org/embedded?editable=1&example=SDK_JAVA/PRECOMPILED_OBJECT_TYPE_EXAMPLE/MinimalWordCount" width=100% height=700px class="code-snippet playground" allow=clipboard-write>< [...]
+<img src=/images/arrow-right.svg alt="Go to the case study"></a></div><div class=case-study-row-button-container><a href="mailto:dev@beam.apache.org?subject=Beam Website Add New Case Study" class=case-study-primary-button>Share your story</a></div><div class=quote-img-container><div class=quote-img><img src=images/case-study/intuit/intuit-quote.png alt="Quote Logo"></div></div></div></div></div><div class=swiper-slide><div class=wrap-slide><div class=quote-card><div class=quote-icon><svg [...]
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