  The Large Hadron Collider (LHC) is one of the most complex machines ever
build. It is composed of many components which constitute a large system. The
tunnel and the accelerator is just one of a very critical fraction of the whole
LHC infrastructure. Hardware comissioning as one of the critical processes
before running the LHC is implemented during the Long Shutdown (LS) states of
the macine, where Electrical Quality Assurance (ELQA) is one of its key
components. Here a huge data is collected when implementing various ELQA
electrical tests. In this paper we present a conceptual framework for
supporting a rapid design of web applications for ELQA data analysis. We show a
framework's main components, their possible integration with other systems and
machine learning algorithms and a simple use case of prototyping an application
for Electrical Quality Assurance of the LHC.
