While a large number of companies offer "big data" solutions, from data analysis tools to specialist storage systems to cloud services, in sectors from manufacturing to logistics, financial services to geophysics, relatively few are concerned with how the data collection works: it is almost assumed that data will be available for import in a nice, friendly format.
Similarly there is a large number of (different) companies developing hardware and supporting software for Raspberry Pi, BeagleBone and similar "education / hobbyist" devices, ranging from weather stations, to door entry systems, to interfaces with "legacy" interfaces such as RS485. [It's written as "legacy" because our view is that if you are still using it, it's not legacy to you, it's live - no matter how old it may be]. There are also several specialist design and small-scale manufacturing companies able to take the Pi-class devices and develop interfaces to these older but operational systems: with some distributed computing and intelligence on these devices, the linking of actual equipment to the "big data" world becomes possible for companies of all sizes. Devices based on the "system on module" model and other industrialised devices can be selected which are mostly software-compatible with the Pi-class, allowing lower cost "proof of concept" stages using the smaller devices before any major costs incurred. Coupled with the use of cloud services, these devices can provide end-to-end proof of concept for larger projects with little or no capital cost, and investment decisions can be taken based on the outcome of proper test, verification and validation phases rather than on business cases alone.
SC3 Technologies can help companies build these bridges between old and new and help create proper business cases prior to larger investments, and also help develop the business cases and alternatives for programmes to take advantage of new capabilities and technologies, even for older systems.
Data collected, reports produced, and archives all need computing and storage resources, and in many (if not most) cases it is difficult to estimate either the power or storage requirements. With the widespread availability of cloud computing, and the ability to implement secure environments with those clouds, these problems become less urgent, and companies can evaluate requirements over time, then determine whether there should be an "in house" / "in cloud" split, and so on.