Streaming Analytics Comparison of Open Source Frameworks, Products, Cloud Services

Posted in Analytics, Big Data, Business Intelligence, Cloud, Hadoop on November 15th, 2016 by Kai Wähner

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:

  • How to Apply Machine Learning to Real Time Processing” (see slides and video recording from a similar conference talk).
  • Comparison of Streaming Analytics Options” (the reason for this blog post; an updated version of my talk from JavaOne 2015)
Tags: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Machine Learning Applied to Microservices

Posted in Analytics, Big Data, Business Intelligence, Cloud, Docker, Hadoop, Microservices, Middleware 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 respectively machine learning.

Tags: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Comparison Of Log Analytics for Distributed Microservices – Open Source Frameworks, SaaS and Enterprise Products

Posted 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:

Tags: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Streaming Analytics with Analytic Models (R, Spark MLlib, H20, PMML)

Posted in Analytics, Big Data, Business Intelligence, Hadoop, In Memory, NoSQL on March 3rd, 2016 by Kai Wähner

In March 2016, I had a talk at Voxxed Zurich about “How to Apply Machine Learning and Big Data Analytics to Real Time Processing”.

Kai_Waehner_at_Voxxed_Zurich

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.

Tags: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Framework and Product Comparison for Big Data Log Analytics and ITOA

Posted in Analytics, Big Data, Hadoop, Microservices on February 4th, 2016 by Kai Wähner

In February 2016, I presented a brand new talk at OOP in Munich: “Comparison of Frameworks and Tools for Big Data Log Analytics and IT Operations Analytics”. The focus of the talk is to discuss different open source frameworks, SaaS cloud offerings and enterprise products for analyzing big masses of distributed log events. This topic is getting much more traction these days with the emerging architecture concept of Microservices.

Key Take-Aways

  • Log Analytics enables IT Operations Analytics for Machine Data
  • Correlation of Events is the Key for Added Business Value
  • Log Management is complementary to other Big Data Components
Tags: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Comparison of Stream Processing Frameworks and Products

Posted in Analytics, Business Intelligence, Hadoop, In Memory on October 25th, 2015 by Kai Wähner

See how products, libraries, and frameworks that full under ‘streaming data analytics’ use cases are categorized and compared.

Streaming Analytics processes data in real time while it is in motion. This concept and technology emerged several years ago in financial trading, but it is growing increasingly important these days due to digitalization and Internet of Things (IoT). The following slide deck from a recent talk at a conference covers:

  • Real world success stories from different industries (Manufacturing, Retailing, Sports)
  • Alternative Frameworks and Products for Stream Processing
  • Complementary Relationship to Data Warehouse, Apache Hadoop, Statistics, Machine Learning, Open Source R, SAS, Matlab, etc.
Tags: , , , , , , , , , , , , , , , , , , , , ,

TIBCO BusinessWorks and StreamBase for Big Data Integration and Streaming Analytics with Apache Hadoop and Impala

Posted 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.

Tags: , , , , , , , , , , , , , , , , , , , , , , , , , ,

Comparison of Stream Processing and Streaming Analytics Alternatives (Apache Storm, Spark, IBM InfoSphere Streams, TIBCO StreamBase, Software AG Apama)

Posted in Analytics, Big Data, Business Intelligence, Hadoop on September 10th, 2014 by Kai Wähner

The demand for stream processing is increasing a lot these days. Frameworks (Apache Storm, Spark) and products (e.g. IBM InfoSphere Streams, TIBCO StreamBase, Software AG Apama) for stream processing and streaming analytics are getting a lot of attention 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. This is required for trading, fraud detection, system monitoring, and many other examples. A “too late architecture” cannot realize these use cases.

Tags: , , , , , , , , , , , , , , , ,

Intelligent Business Process Management Suites (iBPMS) – The Next-Generation BPM for a Big Data World

Posted in Analytics, Big Data, BPM, Business Intelligence, EAI, ESB, Hadoop, Social Network on August 27th, 2014 by Kai Wähner

In August 2014, I had an interesting talk at ECSA 2014 in Vienna about iBPMS called The Next-Generation BPM for a Big Data World: Intelligent Business Process Management Suites (iBPMS). iBPMS is a term introduced by Gartner some time ago: Magic Quadrant for Intelligent Business Process Management Suites.

I want to share the slides with you. As always, I appreciate every comment or feedback…

Abstract: iBPMS / iBPM

Here is the abstract of my session about iBPMS:

Tags: , , , , , , , , , , , , , ,

Fundamentals of Stream Processing (IBM InfoSphere Streams, TIBCO StreamBase, Apache Storm) – Book Review

Posted 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).

Tags: , , , , , , , , , , , , , , , , , , , , , , ,