Visual Analytics + Open Source Deep Learning Frameworks

Posted in Analytics, Big Data, Cloud, Hadoop, Machine Learning on April 24th, 2017 by Kai Wähner

Deep Learning gets more and more traction. It basically focuses on one section of Machine Learning: Artificial Neural Networks. This article explains why Deep Learning is a game changer in analytics, when to use it, and how Visual Analytics allows business analysts to leverage the analytic models built by a (citizen) data scientist.

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: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

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:

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: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Intelligent BPM Suite (iBPMS): Implementation of a CRM Use Case

Posted in Analytics, Big Data, BPM, Business Intelligence, Cloud, ESB, In Memory, Social Network on December 3rd, 2014 by admin

Today, humans have to interpret large sets of different data to make a decision. Using gut feeling is nothing but gambling. Therefore, big data analytics is getting more and more important every year to make better decisions. However, just doing big data analytics is not enough. In many use cases, systematic and monitored human interactions are as important to get best outcomes.

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

“Hadoop and Data Warehouse (DWH) – Friends, Enemies or Profiteers? What about Real Time?” – Slides (including TIBCO Examples) from JAX 2014 Online

Posted in Analytics, Big Data, Business Intelligence, Cloud, ESB, Hadoop on May 13th, 2014 by Kai Wähner

Slides from my talk “Hadoop and Data Warehouse (DWH) – Friends, Enemies or Profiteers? What about Real Time?” at JAX 2014 (Twitter #jaxcon) in Mainz are online. JAX is a great conference with interesting topics and many good speakers!

Content (Data Warehouse, Business Intelligence, Hadoop, Stream Processing)

Big data represents a significant paradigm shift in enterprise technology. Big data radically changes the nature of the data management profession as it introduces new concerns about the volume, velocity and variety of corporate data. New business models based on predictive analytics, such as recommendation systems or fraud detection, are relevant more than ever before. Apache Hadoop seems to become the de facto standard for implementing big data solutions. For that reason, solutions from many different vendors emerged on top of Hadoop.

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