Why: you need to make technological choices for realizing your data science solution (e.g. databases, front-end technologies, visualization libraries, processing platforms, ...), but are confronted with the huge list of available options that are all only slightly different, but promise the same, evolve at a rapid pace, do not necessarily interoperate, etc.
What: we summarize the state-of-the-art and help you make motivated technological choices
- Requirements elicitation: we elicit relevant functional and technological requirements
- Technological state-of-the-art: we identify and compare relevant technological platforms, libraries, toolkits, algorithms, ...
- Reference architecture
- we define a reference architecture and suitable data format(s)
- we instantiate this architecture with selected technological components in an initial proof-of-concept
- State-of-the-art report: a detailed document with links to relevant technologies and an evaluation of alternatives in function of the identified requirements
- A proof-of-concept architecture instantiation: a reference prototype implementation demonstrating the suitability of the designed architecture for the business goals in mind
- Architecture manual: a documented specification of the realized architecture