Video Recording – Apache Kafka as Event-Driven Open Source Streaming Platform (Voxxed Zurich 2018)

Posted in Apache Kafka, Big Data, Cloud, Docker, EAI, ESB, Integration, Java / JEE, Kafka Connect, Kafka Streams, KSQL, Kubernetes, Messaging, Microservices, Middleware, Open Source, SOA, Stream Processing on March 13th, 2018 by admin

I spoke at Voxxed Zurich 2018 about Apache Kafka as Event-Driven Open Source Streaming Platform. The talk includes an intro to Apache Kafka and its open source ecosystem (Kafka Streams, Connect, KSQL, Schema Registry, etc.). Just want to share the video recording of my talk.

Abstract

This session introduces Apache Kafka, an event-driven open source streaming platform. Apache Kafka goes far beyond scalable, high volume messaging. In addition, you can leverage Kafka Connect for integration and the Kafka Streams API for building lightweight stream processing microservices in autonomous teams. The open source Confluent Platform adds further components such as a KSQL, Schema Registry, REST Proxy, Clients for different programming languages and Connectors for different technologies and databases. Live Demos included.

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Apache Kafka Streams + Machine Learning (Spark, TensorFlow, H2O.ai)

Posted in Analytics, Apache Kafka, Apache Spark, Big Data, Confluent, Hadoop, Integration, Kafka Connect, Kafka Streams, Machine Learning, Messaging, Microservices, Open Source, Stream Processing on May 23rd, 2017 by Kai Wähner

I started at Confluent in May 2017 to work as Technology Evangelist focusing on topics around the open source framework Apache Kafka. I think Machine Learning is one of the hottest buzzwords these days as it can add huge business value in any industry. Therefore, you will see various other posts from me around Apache Kafka (messaging), Kafka Connect (integration), Kafka Streams (stream processing), Confluent’s additional open source add-ons on top of Kafka (Schema Registry, Replicator, Auto Balancer, etc.). I will explain how to leverage all this for machine learning and other big data technologies in real world production scenarios.

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Comparison: Data Preparation vs. Inline Data Wrangling in Machine Learning and Deep Learning Projects

Posted in Analytics, Big Data, Business Intelligence, Hadoop on February 13th, 2017 by Kai Wähner

I want to highlight a new presentation about Data Preparation in Data Science projects:

“Comparison of Programming Languages, Frameworks and Tools for Data Preprocessing and (Inline) Data Wrangling  in Machine Learning / Deep Learning Projects”

Data Preparation as Key for Success in Data Science Projects

A key task to create appropriate analytic models in machine learning or deep learning is the integration and preparation of data sets from various sources like files, databases, big data storages, sensors or social networks. This step can take up to 80% of the whole project.

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Characteristics of a Good Visual Analytics and Data Discovery Tool

Posted in Analytics, Big Data, Business Intelligence, Hadoop on July 28th, 2016 by Kai Wähner

Visual Analytics and Data Discovery allow analysis of big data sets to find insights and valuable information. This is much more than just classical Business Intelligence (BI). See this article for more details and motivation: “Using Visual Analytics to Make Better Decisions: the Death Pill Example“. Let’s take a look at important characteristics to choose the right tool for your use cases.

Visual Analytics Tool Comparison and Evaluation

Several tools are available on the market for Visual Analytics and Data Discovery. Three of the most well known options are Tableau, Qlik and TIBCO Spotfire. Use the following list to compare and evaluate different tools to make the right decision for your project:

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