Laying the Groundwork for Creating Utility Analytics Session 2: OT, Analytics and Data (Slides)

Utility analytics do not start with buying an analytic package and hiring a data scientist or two. Instead, they start in the field with the decisions on what data to capture, how much of it is transmitted, where it is processed and storage. Relays and other sensing equipment in the field have many inputs, and some are only connected to a few of these inputs, meaning data is not possible to capture, should those inputs be connected? How do you create a simple diagram that allows the discussion of the inputs and their value? Why are field walk downs needed and what can I do about fixing my topology in my systems – which is the basic requirement for most analytics?
Once the right field data is flowing into the enterprise, what do I do with it, and why can’t I just drop it into an analytics package or an AI system and be done with it? What do you mean there is hard work between raw data and actionable analytics? What are the hard won lessons of real insight?