updating the Wisdom thinking
Data is First in First out. What you just learn you can recall. It is not tested checked or known to be true. It is why we all share things we find without knowing how true of biased it is. Often why we share data that is not as true as we think.
DATA > I carry my smartphone in the car. Smartphone has GPS on and I am running Waze. The data stream is a timestamped set of GPS locations with each userID and possibly some device details. A simple stream of table entries. As you say... data is data and it cannot be refuted.
FIFO > data comes out exactly as it goes in with no value added, maybe data is incorrect and incomplete. The processor will take the data as it comes to create information.
Information is First In, Last out. This slows the immediacy of response and allows us to gather much data before we start to determine. It is a great way of improving quality. Once we have used this information we can feedback what value it created and therefore if useful
INFORMATION > Sliced first by user and time, then by the sequence of GPS coordinates along each road, we get a set of journeys. That is probably information. From it we can determine who goes where and the speed of traffic on a road at a specific time. Unlike the data this information is potentially flawed - the man who loaded a pull-cart up with 99 phones created an online traffic jam. https://www.theverge.com/2020/
2/3/21120463/google-maps- traffic-jams-99-phones-little- red-wagon-simon-weckert FILO > Need a full journey (GPS static for a time period at either end of the data set) to be useful. Need the end stamp before we retrieve. Need to test the quality of the data otherwise what is built on top is flawed. The processor will take the data in chunks to generate journey sets that will form the basis of route future recommendations, these are background activities that are done 'in batch'.
Knowledge is Last In, Last out. Again this slows the response further and waits to get everything before determining is new knowledge is there or just a new fact is present that does not change the overall analysis. Using the knowledge we can feedback what impact it created and therefore if it had the desired outcome, or what the delta is.
KNOWLEDGE > As I am driving, I need to know where to turn to get me fastest to my destination. So present me with the next turn I need to make and give me enough notice to make that turn successfully. If the traffic changes, re-route me one or two turns ahead of where I am now to give me time to respond safely. That is the knowledge I need. I don't want to commit any of this to memory.
LILO > All the historical journeys will be the knowledge . So I have a set of possible routes to my programmed destination, but the one recommended will need to pull data about the traffic speed on each of the routes between where I am and the destination. This is MapQuest or what happens at the start of the Waze UX - give me a startpoint, end point and any route constraints and I will make the best available guess based on the history I have to give you a route.
Wisdom is Last In, First Out. We reverse the order, using the most recent wisdom first. We now measure the outcome when wisdom was used to learn if it worked and also to adjust the next time we get to use wisdom.
WISDOM > Take all the journeys and look at the data a different way, look at the speed of a road over a 24 hour period and over the days of the week. Look at relative road speeds at the same time. Capture information regarding types of vehicle. Capture road accident information. All of this data could be used to optimize traffic flows. Can we use this data to reduce the time-cost of commute, can we use it to better schedule public transport alternatives?
LIFO > To actually make the decision as to what the next turn is, it needs a near real-time set of data on local traffic conditions, so it takes all the knowledge and supplements it with real time traffic data (Data quickly processed to give traffic speed in the immediate vicinity (= information) which is applied to my route (= knowledge) that will tell me how to flex my route as I go (= wisdom)Data is First in First out. What you just learn you can recall. It is not tested checked or known to be true. It is why we all share things we find without knowing how true of biased it is. Often why we share data that is not as true as we think.DATA > I carry my smartphone in the car. Smartphone has GPS on and I am running Waze. The data stream is a timestamped set of GPS locations with each userID and possibly some device details. A simple stream of table entries. As you say... data is data and it cannot be refuted.
FIFO > data comes out exactly as it goes in with no value added, maybe data is incorrect and incomplete. The processor will take the data as it comes to create information.
Information is First In, Last out. This slows the immediacy of response and allows us to gather much data before we start to determine. It is a great way of improving quality. Once we have used this information we can feedback what value it created and therefore if useful
INFORMATION > Sliced first by user and time, then by the sequence of GPS coordinates along each road, we get a set of journeys. That is probably information. From it we can determine who goes where and the speed of traffic on a road at a specific time. Unlike the data this information is potentially flawed - the man who loaded a pull-cart up with 99 phones created an online traffic jam. https://www.theverge.com/2020/
2/3/21120463/google-maps- traffic-jams-99-phones-little- red-wagon-simon-weckert FILO > Need a full journey (GPS static for a time period at either end of the data set) to be useful. Need the end stamp before we retrieve. Need to test the quality of the data otherwise what is built on top is flawed. The processor will take the data in chunks to generate journey sets that will form the basis of route future recommendations, these are background activities that are done 'in batch'.
Knowledge is Last In, Last out. Again this slows the response further and waits to get everything before determining is new knowledge is there or just a new fact is present that does not change the overall analysis. Using the knowledge we can feedback what impact it created and therefore if it had the desired outcome, or what the delta is.
KNOWLEDGE > As I am driving, I need to know where to turn to get me fastest to my destination. So present me with the next turn I need to make and give me enough notice to make that turn successfully. If the traffic changes, re-route me one or two turns ahead of where I am now to give me time to respond safely. That is the knowledge I need. I don't want to commit any of this to memory.
LILO > All the historical journeys will be the knowledge . So I have a set of possible routes to my programmed destination, but the one recommended will need to pull data about the traffic speed on each of the routes between where I am and the destination. This is MapQuest or what happens at the start of the Waze UX - give me a startpoint, end point and any route constraints and I will make the best available guess based on the history I have to give you a route.
Wisdom is Last In, First Out. We reverse the order, using the most recent wisdom first. We now measure the outcome when wisdom was used to learn if it worked and also to adjust the next time we get to use wisdom.
WISDOM > Take all the journeys and look at the data a different way, look at the speed of a road over a 24 hour period and over the days of the week. Look at relative road speeds at the same time. Capture information regarding types of vehicle. Capture road accident information. All of this data could be used to optimize traffic flows. Can we use this data to reduce the time-cost of commute, can we use it to better schedule public transport alternatives?LIFO > To actually make the decision as to what the next turn is, it needs a near real-time set of data on local traffic conditions, so it takes all the knowledge and supplements it with real time traffic data (Data quickly processed to give traffic speed in the immediate vicinity (= information) which is applied to my route (= knowledge) that will tell me how to flex my route as I go (= wisdom)