## Workshop: Maximizing Confidence in Your Data Model Changes with dbt and PipeRider

To learn how to use PipeRider together with dbt for detecting changes in model and data, sign up for a workshop

- Video: https://www.youtube.com/watch?v=O-tyUOQccSs
- Repository: https://github.com/InfuseAI/taxi_rides_ny_duckdb


## Homework

The following questions follow on from the original Week 4 homework, and so use the same data as required by those questions:

https://github.com/DataTalksClub/data-engineering-zoomcamp/blob/main/cohorts/2023/week_4_analytics_engineering/homework.md

Yellow taxi data - Years 2019 and 2020
Green taxi data - Years 2019 and 2020
fhv data - Year 2019.

### Question 1:

What is the distribution between vendor id filtering by years 2019 and 2020 data?

You will need to run PipeRider and check the report

* 70.1/29.6/0.5
* 60.1/39.5/0.4
* 90.2/9.5/0.3
* 80.1/19.7/0.2

### Question 2:

What is the composition of total amount (positive/zero/negative) filtering by years 2019 and 2020 data?

You will need to run PipeRider and check the report


* 51.4M/15K/48.6K
* 21.4M/5K/248.6K
* 61.4M/25K/148.6K
* 81.4M/35K/14.6K

### Question 3:

What is the numeric statistics (average/standard deviation/min/max/sum) of trip distances filtering by years 2019 and 2020 data?

You will need to run PipeRider and check the report


* 1.95/35.43/0/16.3K/151.5M
* 3.95/25.43/23.88/267.3K/281.5M
* 5.95/75.43/-63.88/67.3K/81.5M
* 2.95/35.43/-23.88/167.3K/181.5M



## Submitting the solutions

* Form for submitting: https://forms.gle/WyLQHBu1DNwNTfqe8
* You can submit your homework multiple times. In this case, only the last submission will be used. 

Deadline: 20 March, 22:00 CET


## Solution

Video: https://www.youtube.com/watch?v=inNrUys7W8U&list=PL3MmuxUbc_hJjEePXIdE-LVUx_1ZZjYGW