Source:  https://en.wikipedia.org/wiki/Graph_drawing#/media/File:Social_Network_Analysis_Visualization.png

"The whole thing is more than the sum of its parts"

(Aristoteles)

... that's why we connect the parts and use the additional benefit of the arised network

• Every relevant data object - e.g. coming from R&D, production and use of your products - is documented and linked in a graph - based on a customer specific semantic data model
• Both data objects ("nodes") and directed links ("relations") are named descriptively ("semantic"). 
• All your important but mostly unstructured data (Excel sheets) are integrated into graph - just in the moment of its creation
• The selection of data to be integrated depends on your specific requirements. This could be ..
• • Bill of materials (a graph is the unbeatable way to store this data)
  • Marketing claims with functional requirements
  • Functions objects with technical components
  • Raw materials with details like data sheets and approvals
  • Legal requirements in terms of conformity 
  • etc.
• Finally you can browse the graph by jumping from node to node. You will find the needed information with only a few clicks
• Parameterized queries deliver interactive work lists as a result; so you can avoid to work with (copied) Excel sheets
• This kind of data network guarantees a high data quality and is the the first step towards a company specific knowledge management

Do you think it's impossible to handle such an amount of data in one single "place"?

Just look at the well used social networks like Facebook or Instagram. A few years ago nobody could imagine that billions of people would interact in that way and create millions of data objects every day.

The technical tools for handling networks (graphs) of that scale are available. We only have to adapt the use of Graph databases for industrial purposes. This is what we offer.