There is a large market gap between the sensor platform providers and the would-be end users of that sensor data. Business is constrained by the fact that the end users are not capable of consuming what is being produced and neither party in the transaction is really qualified to solve that problem.
Sensor platform companies can't make their data more consumable because they only know their data, not the analytic nuances of the end users nor the other sensor modalities that the end user may be using. They try, with the hope of improving revenue, but it almost never comes off. The end users are experts in their analysis problems and application domains but usually have no skill or capacity to write custom performance-engineered infrastructure software to bring the sensor data into their domain. This software often has pretty hardcore computer science requirements and there is minimal tooling, certainly not in open source, to make this easier or more scalable. There is clearly a market opportunity, but neither of the obvious parties is in a position to address it even for their own immediate benefit.
There are a few companies with expertise in building high-performance data tooling for analytic workflows across sensor modalities with enough application understanding to bring it into the end user's domain. There is a lot of commonality across application domains from the view of tooling requirements but you have to have expertise in several vertical domains to see it, so it is repeatable. These companies have neither the data nor the application but they bring them close enough together that they can "make the market" as it were. Currently this is a high-end contracting business rather than a general platform, so it doesn't scale. But if this tooling became part of a general platform, it would let the sensor data platforms focus on data collection without worrying about how to make the data more consumable for various application domains, which they were failing at anyway.
The state of software tooling for these sensing data applications is primitive, overfitted for single data sources, and not nearly scalable enough. Most other problems in the sensor data market are consequences of this reality.