Build and Optimize Data Warehouses with BigQuery: Challenge Lab

Build and Optimize Data Warehouses with BigQuery: Challenge Lab | Google Cloud Skills BoostQwiklabs

Task 1: Create a table partitioned by date

CREATE TABLE <DATASET_NAME>.<TABLE_NAME>
PARTITION BY date
OPTIONS(partition_expiration_days=360)
AS
SELECT * 
FROM `bigquery-public-data.covid19_govt_response.oxford_policy_tracker`
WHERE alpha_3_code NOT IN ('GBR','BRA','CAN','USA');

Task 2: Add new columns to your table

ALTER TABLE <DATASET_NAME>.<TABLE_NAME>
ADD COLUMN population INT64,
ADD COLUMN country_area FLOAT64,
ADD COLUMN mobility STRUCT<
   avg_retail      FLOAT64,
   avg_grocery     FLOAT64,
   avg_parks       FLOAT64,
   avg_transit     FLOAT64,
   avg_workplace   FLOAT64,
   avg_residential FLOAT64
>

Task 3: Add country population data to the population column

Query 1

CREATE OR REPLACE TABLE <DATASET_NAME>.pop_data_2019 AS
SELECT
  country_territory_code,
  pop_data_2019
FROM 
  `bigquery-public-data.covid19_ecdc.covid_19_geographic_distribution_worldwide`
GROUP BY
  country_territory_code,
  pop_data_2019
ORDER BY
  country_territory_code

Query 2

UPDATE
   `<DATASET_NAME>.<TABLE_NAME>` t0
SET
   population = t1.pop_data_2019
FROM
   `<DATASET_NAME>.pop_data_2019` t1
WHERE
   CONCAT(t0.alpha_3_code) = CONCAT(t1.country_territory_code);

Task 4: Add country area data to the country_area column

UPDATE
   `<DATASET_NAME>.<TABLE_NAME>` t0
SET
   t0.country_area = t1.country_area
FROM
   `bigquery-public-data.census_bureau_international.country_names_area` t1
WHERE
   t0.country_name = t1.country_name

Task 5: Populate the mobility record data

UPDATE
   `<DATASET_NAME>.<TABLE_NAME>` t0
SET
   t0.mobility.avg_retail      = t1.avg_retail,
   t0.mobility.avg_grocery     = t1.avg_grocery,
   t0.mobility.avg_parks       = t1.avg_parks,
   t0.mobility.avg_transit     = t1.avg_transit,
   t0.mobility.avg_workplace   = t1.avg_workplace,
   t0.mobility.avg_residential = t1.avg_residential
FROM
( SELECT 
   country_region, 
   date,
   AVG(retail_and_recreation_percent_change_from_baseline) as avg_retail,
   AVG(grocery_and_pharmacy_percent_change_from_baseline)  as avg_grocery,
   AVG(parks_percent_change_from_baseline) as avg_parks,
   AVG(transit_stations_percent_change_from_baseline) as avg_transit,
   AVG(workplaces_percent_change_from_baseline) as avg_workplace,
   AVG(residential_percent_change_from_baseline)  as avg_residential
 FROM `bigquery-public-data.covid19_google_mobility.mobility_report`
 GROUP BY country_region, date
) AS t1
WHERE CONCAT(t0.country_name, t0.date) = CONCAT(t1.country_region, t1.date)

Task 6: Query missing data in population & country_area columns

SELECT DISTINCT country_name
FROM `<DATASET_NAME>.<TABLE_NAME>`
WHERE population IS NULL
UNION ALL
SELECT DISTINCT country_name
FROM `<DATASET_NAME>.<TABLE_NAME>`
WHERE country_area IS NULL
ORDER BY country_name ASC