Predictive modeling: Task: Ambulance Demand Data Generating Process: NYC FDNY Emergency Medical Services Ambulance Calls data Asnwer the questions based on the NYC FDNY Emergency Medical Services Ambulance Call data? Dates of Coverage { NYC FDNY Emergency Medical Services Ambulance Calls data } Frequency of data collection {how often is the data collected? After every incident? Daily? Yearly?} Agency / Organization collecting the data {who specifically is collecting the data? Please avoid using general references like “government” or “police} Original Unit of Analysis {What is the original unit of analysis for the data as provided? Calls for service? Census tracts? Cities?} Transformed Unit of Analysis{i.e. are you modifying the call data to support your model? Hint: if you are doing “demand” model you will be aggregating the data.} Data Generation Description{here, I want you in your own words to describe how you think the data was generated. Think 2-3 sentences.} Data Collector{Who collects the data? A dispatcher? A Census taker?} Triggering Process{What triggers the data to be collected? A call for service? A yearly survey process?} Process Alignment{What system captures the data? Is it hand entered? What existing business process does the data align with [i.e. data on ATM transactions come from someone using an ATM; data from calls for service come from dispatch records for calls coming in to 911, etc.]?}
Predictive modeling:
Task: Ambulance Demand
Data Generating Process: NYC FDNY Emergency Medical Services Ambulance Calls data
Asnwer the questions based on the NYC FDNY Emergency Medical Services Ambulance Call data?
Dates of Coverage { NYC FDNY Emergency Medical Services Ambulance Calls data }
Frequency of data collection {how often is the data collected? After every incident? Daily? Yearly?}
Agency / Organization collecting the data {who specifically is collecting the data? Please avoid using general references like “government” or “police}
Original Unit of Analysis {What is the original unit of analysis for the data as provided? Calls for service? Census tracts? Cities?}
Transformed Unit of Analysis{i.e. are you modifying the call data to support your model? Hint: if you are doing “demand” model you will be aggregating the data.}
Data Generation Description{here, I want you in your own words to describe how you think the data was generated. Think 2-3 sentences.}
Data Collector{Who collects the data? A dispatcher? A Census taker?}
Triggering Process{What triggers the data to be collected? A call for service? A yearly survey process?}
Process Alignment{What system captures the data? Is it hand entered? What existing business process does the data align with [i.e. data on ATM transactions come from someone using an ATM; data from calls for service come from dispatch records for calls coming in to 911, etc.]?}
The task at hand in the field of predictive modeling is to forecast ambulance demand in the dynamic context of New York City. A thorough examination of the data generation process is required before embarking on this quest. Each aspect contributes to the creation of an effective prediction model, from the temporal span to the complexities of data gathering and the entities involved.
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