Update homework.md

week_4/homework/homework.md

@@ -1,37 +1,33 @@
 ## Week 4 Homework 
 
-In this homework, we'll use the models developed during the week 4 videos and enhance the already presented dbt project using the already loaded Taxi data for fhv vehicles for year 2019 in our DWH.
+Please see my code for the following:
 
-We will use the data loaded for:
-
-* Building a source table: `stg_fhv_tripdata`
-* Building a fact table: `fact_fhv_trips`
-* Create a dashboard 
+* models/staging/[stg_fhv_tripdata.sql](https://github.com/TylerJSimpson/data_engineering_zoomcamp/blob/main/week_4/homework/models/staging/stg_fhv_tripdata.sql)
+* models/staging/[schema.yml](https://github.com/TylerJSimpson/data_engineering_zoomcamp/blob/main/week_4/homework/models/staging/schema.yml)
+* models/core/[fact_fhv_trips.sql](https://github.com/TylerJSimpson/data_engineering_zoomcamp/blob/main/week_4/homework/models/core/fact_fhv_trips.sql)
+* models/core/[schema.yml](https://github.com/TylerJSimpson/data_engineering_zoomcamp/blob/main/week_4/homework/models/core/schema.yml)
+* dashboard
 
 
 ### Question 1: 
 
 **What is the count of records in the model fact_trips after running all models with the test run variable disabled and filtering for 2019 and 2020 data only (pickup datetime)** 
 
-You'll need to have completed the "Build the first dbt models" video and have been able to run the models via the CLI. 
-You should find the views and models for querying in your DWH.
-
-- 41648442
-- 51648442
-- 61648442
-- 71648442
+Record count of fact_trips in BigQuery details page:  
+61,636,378  
 
+Closest option:  
+**61648442**  
 
 ### Question 2: 
 
 **What is the distribution between service type filtering by years 2019 and 2020 data as done in the videos**
 
-You will need to complete "Visualising the data" videos, either using data studio or metabase. 
+You will need to complete "Visualising the data" videos, either using data studio or metabase.  
+
+My original [dashboard](https://lookerstudio.google.com/s/kfnV1LcxmcI) answers this question.  
 
-- 89.9/10.1
-- 94/6
-- 76.3/23.7
-- 99.1/0.9
+**89.9/10.1**
 
 
 
@@ -42,11 +38,15 @@ You will need to complete "Visualising the data" videos, either using data studi
 Create a staging model for the fhv data for 2019 and do not add a deduplication step. Run it via the CLI without limits (is_test_run: false).
 Filter records with pickup time in year 2019.
 
-- 33244696
-- 43244696
-- 53244696
-- 63244696
+```sql
+SELECT  COUNT(*) 
+FROM    `dtc-de-0315.dbt_cloud_pr_218904_5.stg_fhv_tripdata`
+```
+Result:  
+43244693  
 
+Closest option:  
+**43244696**  
 
 ### Question 4: 
 
@@ -56,31 +56,15 @@ Create a core model for the stg_fhv_tripdata joining with dim_zones.
 Similar to what we've done in fact_trips, keep only records with known pickup and dropoff locations entries for pickup and dropoff locations. 
 Run it via the CLI without limits (is_test_run: false) and filter records with pickup time in year 2019.
 
-- 12998722
-- 22998722
-- 32998722
-- 42998722
+Record count of fact_fhv_trips in BigQuery details page:  
+**22,998,722**  
 
 ### Question 5: 
 
 **What is the month with the biggest amount of rides after building a tile for the fact_fhv_trips table**
 Create a dashboard with some tiles that you find interesting to explore the data. One tile should show the amount of trips per month, as done in the videos for fact_trips, based on the fact_fhv_trips table.
 
-- March
-- April
-- January
-- December
-
-
-
-## Submitting the solutions
-
-* Form for submitting: https://forms.gle/6A94GPutZJTuT5Y16
-* You can submit your homework multiple times. In this case, only the last submission will be used. 
-
-Deadline: 25 February (Saturday), 22:00 CET
-
+Created a [visual](https://lookerstudio.google.com/s/jYdIDO070NY) and also double checked in BigQuery. January is by far the largest month.
 
-## Solution
+**January**
 
-We will publish the solution here