We implement your professional analysis environment with the professional support of eoda or in your own contribution. The focus lies on the two areas: Operating system and data science.
The creating of different environments for the different maturity levels of the analyses, which extend from the development to the live environment.
Authentication and authorization
Mapping of workflows with individual role definitions and a granular authorization concept.
Unique central configuration of various database drivers to create proximity and user-friendly access to data.
Data science stack
Data science languages
Based on the assessment, eoda identifies which programming language is suits best for the requirements in your individual analysis scenario.
The productive application of data science languages such as R and Python imposes special requirements on the use of the packages. These include management dependencies or the continuous deployment of critical updates.
For the professional use of analysis scripts, it is recommended to use version management to document changes to the source code in a comprehensible and transparent way and also being able to annul them if necessary.