Know-how for Open Source Analytics
Also with regard to software for Data Analyses, Open Source Technologies complement the technologies offered by software vendors: Producer companies offer chargeable software normally at a high level of quality, along with professional services. Further development is decided in terms of marketability.
By contrast, software which is developed from the Open Source Model is mostly free of charge in the basic version, and the aim of the developing community is often not uniform, but for that more dynamic. This leads on the one hand to this software being widespread in the area of research and development. On the other hand, new functions, particularly in the area of statistical analysis, are made quickly available and are therefore frequently tested and documented to a lesser standard.
R Project – Data analysis with Open Source Software
The Open Source Platform R is a powerful system for data analysis. Hereby, R combines a matrix orientated programming language with modern statistical methods. In particular the graphical tools for explorative data analysis are outstanding.
R has become a standard platform for academic research organisations and has gained acceptance in the industry during the last years. Thereby R offers the following opportunities:
- large collection of libraries for statistical data analysis
- a description language for statistical modes
- simple to learn techniques of graphical features
- an effective object orientated programming language which allows for manifold extensibilities
Many of our employees have years of experience in the implementation of the data analysis software from the "R Project", and can offer our clients solutions and advice partially comparable to vendor software on this basis. We are able to give answers to the following questions:
- What must be considered in the implementation of R within environments which have high quality requirements?
- How does one develop high quality functions with R?
- How does one make functions developed with R available to the end user within the scope of standardised business processes?
- How can functions developed with R be converted to SAS?
- How can R functions be invoked from SAS?
- How does one organise training for R and how do R developers become fit in SAS, and vice versa?
Inform yourself about how we can support you with our services for the R-Software in the Banking Industry and with Manufacturers of Medical devices.
Data integration and Reporting with Open Source Tools
Also in this area, we possess the relevant application know-how. To implement business intelligence on the basis of Open Source Technology, we recommend the following components:
- Data storage: MySQL (relational), Mondrian (OLAP))
- Data Integration: Pentaho
- Reporting: Eclipse BIRT
- Data visualisation: R
- Data Mining: Weka