JillyKim · JillyKim · Apr 12, 2026 · Apr 11, 2026 · Apr 11, 2026
diff --git a/02_activities/assignments/DC_Cohort/Assignment2.md b/02_activities/assignments/DC_Cohort/Assignment2.md
@@ -56,7 +56,7 @@ The store wants to keep customer addresses. Propose two architectures for the CU
 **HINT:** search type 1 vs type 2 slowly changing dimensions. 
 
 ```
-Your answer...
+The one that will retain changes is type2 SCD. It preserves historical changes by creating a new record for each change. The one that will overwrite is type1 SCD. Type1 overwrites old data with new data; thus no historical data is preserved. 
 ```
 
 ***
@@ -192,4 +192,8 @@ Consider, for example, concepts of labour, bias, LLM proliferation, moderating c
 
 ```
 Your thoughts...
+The article, “Neural nets are just people all the way down”, written by Vicki Boykis argues that machine learning, despite its futuristic image, is fundamentally powered by substantial amounts of human labor that are hidden and often ignored. 
+An example that Boykis shows in the article is ImageNet, the landmark image dataset that underpins much of modern computer vision. ImageNet, the brainchild of a professor, Dr. Fei-Fei Li, was actually labeled by hundreds of thousands of crowdsourced workers on Amazon Mechanical Turk who were paid pennies per image. To date, more than 14 million images have been labeled by ImageNet. Moreover, Boykis explains that ImageNet was initially built on WordNet, a linguistic database assembled by Princeton linguists through manual classification work. WordNet itself relied on the Brown Corpus, a dataset of tagged English text compiled by hand in the 1960s.
+This shows that machine learning is in fact invovles human interventions in almost every step. And because people built these systems, they reflect the biases that humans have. As illustrated in the article, the ImageNet Roulette randomly pegged one man as an ‘orphan’ and another as a ‘nonsmoker’. This shows that artificial intelligence is not value-neutral, but can instead reflect and even reinforce people’s biases. Another important ethical issue in the story is concepts of labor. As Amazon Mechanical Turk represents in the essay, behind the AI model training, there are people doing repetitive jobs for living. However, this labor is rarely fairly compensated or recognized. This reality contrasts with the vision of many AI companies, which emphasize how AI advancement can benefit humanity as a whole.
+
 ```
diff --git a/02_activities/assignments/DC_Cohort/assignment2.sql b/02_activities/assignments/DC_Cohort/assignment2.sql
@@ -12,7 +12,6 @@ SELECT
 product_name || ', ' || product_size|| ' (' || product_qty_type || ')'
 FROM product
 
-
 But wait! The product table has some bad data (a few NULL values). 
 Find the NULLs and then using COALESCE, replace the NULL with a blank for the first column with
 nulls, and 'unit' for the second column with nulls. 
@@ -23,8 +22,11 @@ Edit the appropriate columns -- you're making two edits -- and the NULL rows wil
 All the other rows will remain the same. */
 --QUERY 1
 
-
-
+SELECT
+product_name || ', ' || 
+coalesce(product_size,'')||' (' ||
+coalesce(product_qty_type, "unit" )|| ')' as list_of_products
+FROM product;
 
 --END QUERY
 
@@ -40,9 +42,10 @@ each new market date for each customer, or select only the unique market dates p
 HINT: One of these approaches uses ROW_NUMBER() and one uses DENSE_RANK(). 
 Filter the visits to dates before April 29, 2022. */
 --QUERY 2
-
-
-
+SELECT DISTINCT customer_id, market_date,
+dense_rank() OVER (PARTITION BY customer_id ORDER BY market_date ASC) as customer_visit
+FROM customer_purchases
+WHERE market_date < '2022-04-29';
 
 --END QUERY
 
@@ -53,9 +56,13 @@ only the customer’s most recent visit.
 HINT: Do not use the previous visit dates filter. */
 --QUERY 3
 
-
-
-
+SELECT DISTINCT customer_id, market_date, customer_visit
+FROM
+	(SELECT  customer_id, market_date,
+	dense_rank() OVER (PARTITION BY customer_id ORDER BY market_date DESC) as customer_visit
+	FROM customer_purchases
+)
+WHERE customer_visit = 1;
 --END QUERY
 
 
@@ -66,12 +73,13 @@ You can make this a running count by including an ORDER BY within the PARTITION
 Filter the visits to dates before April 29, 2022. */
 --QUERY 4
 
-
-
+SELECT customer_id, product_id, 
+count () OVER (PARTITION BY customer_id, product_id ORDER BY market_date, transaction_time ASC) as num_of_purchases
+FROM customer_purchases
+WHERE market_date < '2022-04-29';
 
 --END QUERY
 
-
 -- String manipulations
 /* 1. Some product names in the product table have descriptions like "Jar" or "Organic". 
 These are separated from the product name with a hyphen. 
@@ -84,17 +92,20 @@ Remove any trailing or leading whitespaces. Don't just use a case statement for
 
 Hint: you might need to use INSTR(product_name,'-') to find the hyphens. INSTR will help split the column. */
 --QUERY 5
-
-
-
+SELECT product_name,
+CASE WHEN instr(product_name, '- J') >0 THEN substr(product_name, -3)
+		WHEN instr(product_name, '- O') >0 THEN substr(product_name, -7)
+END as description
+FROM product;
 
 --END QUERY
 
 
 /* 2. Filter the query to show any product_size value that contain a number with REGEXP. */
 --QUERY 6
-
-
+SELECT *
+FROM product
+WHERE product_size REGEXP '[0-9]';
 
 
 --END QUERY
@@ -111,8 +122,28 @@ HINT: There are a possibly a few ways to do this query, but if you're struggling
 with a UNION binding them. */
 --QUERY 7
 
-
-
+--(1)find the market dates with the highest total sales
+SELECT market_date, total_sales, highest_sales as [row_number]
+FROM (
+	SELECT market_date,
+			SUM(quantity*cost_to_customer_per_qty) AS total_sales,
+			row_number() OVER(ORDER BY (SUM(quantity*cost_to_customer_per_qty)) DESC) as highest_sales
+	FROM customer_purchases
+	GROUP BY market_date
+		)
+WHERE highest_sales = 1
+--(3) Use a UNION to display the two values
+UNION
+--(2) find the market dates with the lowest total sales
+SELECT market_date, total_sales, lowest_sales
+FROM (
+	SELECT market_date,
+			SUM(quantity*cost_to_customer_per_qty) AS total_sales,
+			row_number() OVER(ORDER BY (SUM(quantity*cost_to_customer_per_qty)) ASC) as lowest_sales 
+FROM customer_purchases
+GROUP BY market_date
+	)
+WHERE lowest_sales = 1;
 
 --END QUERY
 
@@ -132,9 +163,29 @@ How many customers are there (y).
 Before your final group by you should have the product of those two queries (x*y).  */
 --QUERY 8
 
-
-
-
+--(1) Create a Temp table with vendor name, product name, and original price
+DROP TABLE IF EXISTS temp.new_inventory;
+CREATE TABLE temp.new_inventory AS
+SELECT DISTINCT
+v.vendor_name,
+v.vendor_id,
+p.product_id, 
+product_name,
+original_price
+FROM vendor_inventory AS vi
+INNER JOIN vendor AS v
+		ON v.vendor_id = vi.vendor_id
+INNER JOIN product AS p
+		ON p.product_id = vi.product_id;
+--(2) Cross join the number of customers to calculate profit that each vendor make per product 
+SELECT vendor_name, product_name, original_price, 
+cp.n_of_customers, 
+5*cp.n_of_customers*original_price AS profit_per_product
+FROM new_inventory
+		CROSS JOIN (SELECT COUNT (DISTINCT customer_id) AS n_of_customers
+		FROM customer_purchases
+		) AS cp;
+
 --END QUERY
 
 
@@ -145,30 +196,45 @@ It should use all of the columns from the product table, as well as a new column
 Name the timestamp column `snapshot_timestamp`. */
 --QUERY 9
 
+--(1) add new column for the CURRENT_TIMESTAMP using Insert into
+DROP TABLE IF EXISTS temp.time_stamp;
+CREATE TEMP TABLE time_stamp (snapshot_timestamp TEXT);
 
-
+INSERT INTO TEMP.time_stamp
+VALUES (CURRENT_TIMESTAMP);
+--(2) create a table 'product units', joining with time_Stamp
+DROP TABLE IF EXISTS temp.product_units;
+CREATE TEMP TABLE product_units AS
+SELECT *
+FROM product
+CROSS JOIN time_stamp
+WHERE product_qty_type = 'unit';
+--(3) verify the result
+SELECT*
+FROM product_units;
 
 --END QUERY
 
 
 /*2. Using `INSERT`, add a new row to the product_units table (with an updated timestamp). 
 This can be any product you desire (e.g. add another record for Apple Pie). */
 --QUERY 10
+INSERT INTO product_units
+VALUES (11, 'Eggs - Organic' , '1dozen', 6, 'unit', CURRENT_TIMESTAMP);
 
-
-
+UPDATE product_units
+SET snapshot_timestamp = CURRENT_TIMESTAMP
+WHERE product_id = 11;
 
 --END QUERY
 
-
 -- DELETE
 /* 1. Delete the older record for the whatever product you added. 
 
 HINT: If you don't specify a WHERE clause, you are going to have a bad time.*/
 --QUERY 11
-
-
-
+DELETE FROM product_units
+WHERE product_id = 10;
 
 --END QUERY
 
@@ -178,7 +244,7 @@ HINT: If you don't specify a WHERE clause, you are going to have a bad time.*/
 First, add a new column, current_quantity to the table using the following syntax.
 
 ALTER TABLE product_units
-ADD current_quantity INT;
+ADD current_quantity INT
 
 Then, using UPDATE, change the current_quantity equal to the last quantity value from the vendor_inventory details.
 
@@ -190,11 +256,34 @@ Finally, make sure you have a WHERE statement to update the right row,
 	you'll need to use product_units.product_id to refer to the correct row within the product_units table. 
 When you have all of these components, you can run the update statement. */
 --QUERY 12
+ALTER TABLE product_units
+ADD current_quantity INT;
 
+--(1) get the last quantity per product using CTE
+UPDATE product_units
+SET current_quantity = coalesce(current_quantity,0);
+
+WITH last_quantity AS (
+SELECT market_date,
+vendor_id,
+product_id,
+quantity,
+latest_day
+FROM (
+	SELECT market_date, vendor_id, product_id, quantity, 
+		RANK()OVER(PARTITION BY vendor_id, product_id ORDER BY market_date DESC) AS latest_day
+	FROM vendor_inventory
+		)
+	WHERE latest_day = 1
+	)
+UPDATE product_units
+SET current_quantity = last_quantity.quantity
+FROM last_quantity
+WHERE product_units.product_id = last_quantity.product_id;
 
+--END QUERY
 
 
---END QUERY
 
 
 
diff --git a/02_activities/assignments/DC_Cohort/bookstore_logical_model.png b/02_activities/assignments/DC_Cohort/bookstore_logical_model.png