Abstract
- The greatest impact to value is being able to build and deploy solutions quickly and at scale
- The foundation of this is standardization
- We learned in past projects that we can solve problems, but scaling and operating those solutions is difficult
- Solutions were built using different technologies
- Solutions treated data differently (a truck was not a truck)
- Solutions were not built for operational sustainment
- The online environment is full of bad actors and other risks, we have seen recent evidence of this
- Platform engineering provides solution developers with a toolkit to be able to rapidly develop and deploy their solutions in a way that is secure, scalable and supportable
- Adoption of cloud technologies in the platform provides the ability to extend our reach across the globe
- Customers, large and small, benefit from the scalability of the cloud to roll out solutions at one site or across the entire organization with ease.
- Artificial Intelligence is helping to optimize processes from pit to port and a cloud-based platform provides on-demand capacity to solve even the hardest problems
- We no longer need to invest in massive compute farms that sit idle most of the time
- We use what we need when we need it
- Massive amounts of standardized data available to the platform can be used for explorative data analysis and training of models.
- Models trained on larger sample sets provide better recommendations for small consumers
- Example: a model to predict engine failure that is trained on 1000 trucks worth of data will make a better recommendation than a model trained on 10 trucks worth of data