In November 2016, I am at Big Data Spain in Madrid for the first time. A great conference with many awesome speakers and sessions about very hot topics such as Apache Hadoop, Spark Spark, Streaming Processing / Streaming Analytics and Machine Learning. If you are interested in big data, then this conference is for you! My two talks:
In November 2016, I attended Devoxx conference in Casablanca. Around 1500 developers participated. A great event with many awesome speakers and sessions. Hot topics this year besides Java: Open Source Frameworks, Microservices (of course!), Internet of Things (including IoT Integration), Blockchain, Serverless Architectures.
I had three talks:
- How to Apply Machine Learning to Real Time Processing
- Comparison of Open Source IoT Integration Frameworks
- Tools in Action – Live Demo of Open Source Project Flogo
In addition, I was interviewed by the Voxxed team about Big Data, Machine Learning and Internet of Things. The video will be posted on Voxxed website in the next weeks.
In October 2016, the open source IoT integration framework Flogo was published as first developer preview. This blog post is intended to give a first overview about Flogo. You can either browse through the slide deck or watch the videos.
What is Project Flogo?
In short, Flogo is an ultra-lightweight integration framework powered by Go programming language. It is open source under the permissive BSD license and easily extendable for your own use cases. Flogo is used to develop IoT edge apps or cloud-native / serverless microservices. Therefore, it is complementary to other integration solutions and IoT cloud platforms.
I had two sessions at O’Reilly Software Architecture Conference in London in October 2016. It is the first #OReillySACon in London. A very good organized conference with plenty of great speakers and sessions. I can really recommend this conference and its siblings in other cities such as San Francisco or New York if you want to learn about good software architectures and new concepts, best practices and technologies. Some of the hot topics this year besides microservices are DevOps, serverless architectures and big data analytics respectively machine learning.
Comparison Of Log Analytics for Distributed Microservices – Open Source Frameworks, SaaS and Enterprise ProductsPosted in Analytics, Big Data, Business Intelligence, Cloud, Hadoop, Microservices, SOA on October 20th, 2016 by Kai Wähner
I had two sessions at O’Reilly Software Architecture Conference in London in October 2016. It is the first #OReillySACon in London. A very good organized conference with plenty of great speakers and sessions. I can really recommend this conference and its siblings in other cities such as San Francisco or New York if you want to learn about good software architectures and new concepts, best practices and technologies. Some of the hot topics this year besides microservices are DevOps, serverless architectures and big data analytics.
I want to share the slide of my session about comparing open source frameworks, SaaS and Enterprise products regarding log analytics for distributed microservices:
In March 2016, I had a talk at Voxxed Zurich about “How to Apply Machine Learning and Big Data Analytics to Real Time Processing”.
Finding Insights with R, H20, Apache Spark MLlib, PMML and TIBCO Spotfire
“Big Data” is currently a big hype. Large amounts of historical data are stored in Hadoop or other platforms. Business Intelligence tools and statistical computing are used to draw new knowledge and to find patterns from this data, for example for promotions, cross-selling or fraud detection. The key challenge is how these findings can be integrated from historical data into new transactions in real time to make customers happy, increase revenue or prevent fraud.
TIBCO BusinessWorks and StreamBase for Big Data Integration and Streaming Analytics with Apache Hadoop and ImpalaPosted in Analytics, Big Data, Business Intelligence, Hadoop, In Memory, NoSQL on April 14th, 2015 by Kai Wähner
Apache Hadoop is getting more and more relevant. Not just for Big Data processing (e.g. MapReduce), but also for Fast Data processing (e.g. Stream Processing). Recently, I published two blog posts on the TIBCO blog to show how you can leverage TIBCO BusinessWorks 6 and TIBCO StreamBase to realize Big Data and Fast Data Hadoop use cases.
Fundamentals of Stream Processing (IBM InfoSphere Streams, TIBCO StreamBase, Apache Storm) – Book ReviewPosted in Analytics, Big Data, Hadoop on July 1st, 2014 by Kai Wähner
Internet of things, cloud and mobile are the major drivers for stream processing. Use cases are network monitoring, intelligent surveillance, but also less technical things such as inventory management or fraud detection. The book helps a lot to get a basic understanding about history, concepts and patterns of the stream processing paradigm.
“Fundamentals of Stream Processing: Application Design, Systems, and Analytics” (www.amazon.com/Fundamentals-Stream-Processing-Application-Analytics/dp/1107015545) is one of only few books available about stream processing. Published in 2014 by Cambridge University Press. Authors are Henrique C. M. Andrade (JP Morgan, New York), Bugra Gedik (Bilkent University, Turkey), Deepak S. Turaga (IBM Thomas J. Watson Research Center, New York).