The management and analysis of data requires tools and skills, which continuously evolve.  To find suitable tools and acquire the needed skills we observe continuously published material on the internet.

Massive open online courses (MOOC), youtube videos, ebooks, documentation of analytics software and programming libraries are freely available and. These resources allow us to build and maintain a data analytics environment, to deal with data from diverse sources. The necessary skills to work with such an environment require permanent training and willingness to explore new approaches.

Analytics Software and libraries

Here we provide an overview of our working environment, which we have used in recent years. Some of the listed tools we are currently evaluating. We do not provide detailed instructions on how to set-up the tools, we rather maintain a list of links to useful documentation and video tutorials.

Microsoft Excel -> Excel has evolved to a powerful package to deal numbers and tabular data

Weka -> Weka contains tools for data preparation, classification, regression, clustering, association rules mining, and visualization. A good book and MOOC allows a fast access to the possibilities offered by Weka.

KNIME -> KNIME Analytics Platform is the open source software for creating data science applications and services.  

MOOCs, eBooks, Documentation

This  list provides links to material explaining the techniques and strategies applied for the analyses of data from various sources. When ever possible we link to resources which offer hands-on explanations, but also introduce or refer to theoretical concepts.

Microsoft Virtual Academy -> Video tutorial about data science, machine learning, data handling andmore. -> Videos from universities.> Frank Kane provides lots of hand-on explainations about data science, machine-learning, with python libraries tensorflow and keras. -> MOOC about data mining with Weka.