We bring together multiple data sources to assemble data sets that are large enough to yield statistically significant conclusions. This often includes combining data from end users or equipment vendors who have smaller data sets from different regions or for different types of equipment.

One challenge in sharing data from different sources is managing data confidentiality. Operators do not generally consider safety, environmental performance and equipment reliability data as providing a advantage. This information can often be shared among the operators. Sensitive data can be anonymized, but this is a double-edged sword. Hiding the data source addresses confidentiality concerns, but lessens the value of the data by hiding what could be very important information. Proprietary data, such as equipment specifications, can be kept confidential by using it as inputs for engineering models and only sharing the results of the models.