Cube accident percentage by vehicle
Posted: Sun Dec 22, 2024 10:39 am
If we sort the cube on the final measure we get a more informative insight when looking at the top 10 values in the final column:
Six of these are predominantly motorbike manufacturers. Of the remaining, Iveco are mainly lorries, Mercedes Benz (which has a mixture of cars and lorries). We discussed Volvo france phone number list in the previous paragraph. Finally, London taxis comes top of the list as having the highest accidents to vehicles ratio.
Whilst the focus of this example is how we can use data from one system in analysis on another system, the above insights are not the end of the story.
Further exploration in the MOT system shows that London taxis, and many of the vehicle makes which are entirely (or largely) trucks, have a much higher average mileage than other makes. This is intuitive as these vehicles will be on the road much more and be driven much further. On average, motorbike makes are ridden less than car makes and so an alternative approach could be to look at accidents per miles driven. We could use the technique above to incorporate that data into our analysis.
Conclusion
The development of file-based expressions has given the user extra flexibility and power in defining expressions which can have their parameters change, whilst the text of the expression remains unchanged and therefore is safer to use in scenarios where it is embedded into production analytics and campaigning.
Six of these are predominantly motorbike manufacturers. Of the remaining, Iveco are mainly lorries, Mercedes Benz (which has a mixture of cars and lorries). We discussed Volvo france phone number list in the previous paragraph. Finally, London taxis comes top of the list as having the highest accidents to vehicles ratio.
Whilst the focus of this example is how we can use data from one system in analysis on another system, the above insights are not the end of the story.
Further exploration in the MOT system shows that London taxis, and many of the vehicle makes which are entirely (or largely) trucks, have a much higher average mileage than other makes. This is intuitive as these vehicles will be on the road much more and be driven much further. On average, motorbike makes are ridden less than car makes and so an alternative approach could be to look at accidents per miles driven. We could use the technique above to incorporate that data into our analysis.
Conclusion
The development of file-based expressions has given the user extra flexibility and power in defining expressions which can have their parameters change, whilst the text of the expression remains unchanged and therefore is safer to use in scenarios where it is embedded into production analytics and campaigning.