Kai Waehner

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University of Bamberg

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Global Field CTO at Confluent working with customers, prospects, partners across the…

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Berufserfahrung

  • Confluent Grafik

    Confluent

    Global (based in Germany)

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    Munich Area, Germany

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    Erlangen Area, Germany

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    Munich Area, Germany

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    Munich Area, Germany

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    Germany

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    Nürnberg Area, Germany

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    Bamberg Area, Germany

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    Nuremberg, Germany

Ausbildung

  • University of Bamberg

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Veröffentlichungen

  • Apache Kafka vs. Enterprise Service Bus (ESB)—Friends, Enemies, or Frenemies?

    Confluent Blog

    This blog post shows why so many enterprises leverage the open source ecosystem of Apache Kafka for successful integration of different legacy and modern applications, and how this differs but also complements existing integration solutions like ESB or ETL tools.

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  • How to Avoid the Anti-Pattern in Analytics: Three Keys for Machine Learning

    RTInsights

    When a different analytic model is used in training versus deployment, results can be disastrous. Here’s how to avoid the anti-pattern.

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  • Using Visual Analytics for Better Decisions: an Online Guide

    RTInsights

    How visual analytics helps businesses make better decisions, and what to look for when evaluating different tools.

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  • How to Apply Machine Learning to Event Processing

    RTInsights

    How do you combine historical Big Data with machine learning for real-time analytics? An approach is outlined with different software vendors, business use cases, and best practices.

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  • Do Good Microservices Architectures Spell the Death of the Enterprise Service Bus?

    Voxxed

    These days, it seems like everybody is talking about microservices. You can read a lot about it in hundreds of articles and blog posts. This article is about the challenges, requirements and best practices for creating a good microservices architecture, and what role an Enterprise Service Bus (ESB) plays in this game.

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  • Real-Time Stream Processing as Game Changer in a Big Data World with Hadoop and Data Warehouse

    InfoQ

    The demand for stream processing is increasing a lot these days. The reason is that often processing big volumes of data is not enough. Data has to be processed fast, so that a firm can react to changing business conditions in real time. A “too late architecture” cannot realize these use cases. This article discusses what stream processing is, how it fits into a big data architecture with Hadoop and a data warehouse (DWH), when stream processing makes sense, and what technologies and products…

    The demand for stream processing is increasing a lot these days. The reason is that often processing big volumes of data is not enough. Data has to be processed fast, so that a firm can react to changing business conditions in real time. A “too late architecture” cannot realize these use cases. This article discusses what stream processing is, how it fits into a big data architecture with Hadoop and a data warehouse (DWH), when stream processing makes sense, and what technologies and products you can choose from.

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  • Spoilt for Choice – How to choose the right Big Data / Hadoop Platform?

    InfoQ

    Big data becomes a relevant topic in many companies this year. Although there is no standard definition of the term „big data“, Hadoop is the de facto standard for processing big data. Almost all big software vendors such as IBM, Oracle, SAP, or even Microsoft use it. However, when you have decided to use Hadoop, the first question is how to start and which product to choose for your big data processes. Several alternatives exist for installing a version of Hadoop and realizing big data…

    Big data becomes a relevant topic in many companies this year. Although there is no standard definition of the term „big data“, Hadoop is the de facto standard for processing big data. Almost all big software vendors such as IBM, Oracle, SAP, or even Microsoft use it. However, when you have decided to use Hadoop, the first question is how to start and which product to choose for your big data processes. Several alternatives exist for installing a version of Hadoop and realizing big data processes. This article discusses different alternatives and recommends when to use which one.

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  • Choosing the Right ESB for Your Integration Needs

    InfoQ

    Different applications within companies and between different companies need to communicate with each other. The Enterprise Service Bus (ESB) has been established as a tool to support application integration. But what is an ESB? When is it better to use an integration suite? And which product is best suited for the next project? This article explains why there is no silver bullet and why an ESB can also be the wrong choice. Selecting the right product is essential for project success.

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  • Free integration frameworks on the Java platform

    The H Developer

    In addition to the increased data traffic between and within companies and organisations, the number of applications to be integrated has also been rising steadily. Despite the multitude of technologies, protocols and data formats, the integration of these applications should ideally allow standardised modelling, efficient implementation and automated testing. Spring Integration, Mule and Apache Camel are three open source integration frameworks that provide this functionality in the Java world.

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  • Lessons Learned: Best Practices for a Successful Introduction of Business Process Management (BPM)

    Service Technology Magazine

    Business Process Management (BPM) is complex, expensive, and often fails! If you agree (in the year of 2012+), then you should read the following rules to do BPM correctly in your next project.

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