Assignment two Completed

02_activities/assignments/DC_Cohort/Assignment1.md

@@ -209,5 +209,5 @@ Consider, for example, concepts of fariness, inequality, social structures, marg
 
 
 ```
-Your thoughts...
+Databases might seem like just a technical tool for storing information, but after reading this article, I started to realize they actually reflect certain values and assumptions. For example, the system described in the article assumes that everyone fits into a traditional family structure, which is not true for many people. Because of this, some individuals were excluded or faced difficulties when the database could not recognize their situation. This made me think that databases can create unfairness, even if that is not the intention. In my everyday life, I also see similar situations, like when filling out forms that only allow limited options for gender or family background. These systems simplify people’s identities, but in doing so, they may ignore important differences and experiences. As someone new to this topic, I am beginning to understand that technology is not neutral, and the way databases are designed can shape how people are treated in society.
 ```

02_activities/assignments/DC_Cohort/Assignment2.md

@@ -56,8 +56,15 @@ 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...
-```
+Your answer 
+***
+I think there are two main ways the bookstore could design a CUSTOMER_ADDRESS table, depending on whether it wants to keep only the latest address or keep a history of address changes.
+
+The first option is the simpler one: one row per customer, where the address just gets overwritten whenever the customer moves. In that version, the table could have fields like customer_id, street_address, city, province, postal_code, country, and maybe last_updated_date. If the customer changes address, the old address is replaced in that same row. This approach is easy to manage and works well if the store only cares about the customer’s current mailing address. But the downside is that once the address is updated, the old one is gone. This would be a Type 1 slowly changing dimension, because the new data overwrites the old data.
+
+The second option is to keep address history. In that version, the table would allow multiple address records for the same customer over time. So instead of using customer_id as the primary key, the table could have something like customer_address_id as the primary key, plus customer_id as a foreign key. Then it could also include effective_start_date, effective_end_date, and maybe an is_current flag. Each time the customer moves, a new row would be inserted instead of updating the old one. That means the bookstore can still see previous addresses if it ever needs them for reporting, auditing, or historical analysis. This would be a Type 2 slowly changing dimension, because changes are handled by adding a new record and preserving the old one.
+
+So overall, Type 1 means overwrite the address and keep only the latest version, while Type 2 means insert a new row and retain the address history.
 
 ***
 
@@ -193,3 +200,8 @@ Consider, for example, concepts of labour, bias, LLM proliferation, moderating c
 ```
 Your thoughts...
 ```
+Reading Neural nets are just people all the way down really shifted how I think about AI. Before this, I often understood AI as something highly technical and distant from ordinary human work, almost as if it were operating on its own. But this article made me realize that behind these systems are many layers of human labour that are often hidden. What looks like “intelligent” output is actually built on people labeling data, filtering harmful content, making judgment calls, and shaping what the model learns. That was one of the biggest ethical issues for me: the invisibility of labour. The article shows that AI is not just a machine process. It depends on human workers, and often those workers do difficult, repetitive, and emotionally harmful tasks without much recognition.
+
+Another issue that stood out to me is bias. If neural nets are trained through human decisions, then they also absorb human assumptions, categories, and inequalities. That means AI does not simply reflect the world neutrally. It can reproduce the social biases already built into society, including racial, cultural, and linguistic hierarchies. As a PhD student in Higher Education at OISE, this made me think about how technologies that seem efficient or innovative can still reinforce exclusion if we do not ask who is designing them, who is labeling the data, and whose standards are treated as normal.
+
+I was also struck by the ethical problem of content moderation. The article reminded me that keeping AI systems “clean” or “safe” often requires humans to be exposed to disturbing material. So the convenience users experience may come at a psychological cost to invisible workers elsewhere. More broadly, this connects AI to society in a very direct way. LLMs are not separate from social systems. They are built through labour, shaped by power, and deployed into unequal worlds. For me, the article was a strong reminder that ethical questions about AI are always also questions about people.

02_activities/assignments/DC_Cohort/assignment1.sql

@@ -6,28 +6,28 @@
 --SELECT
 /* 1. Write a query that returns everything in the customer table. */
 --QUERY 1
-
-
-
-
+SELECT *
+FROM customer
 --END QUERY
 
 
 /* 2. Write a query that displays all of the columns and 10 rows from the customer table, 
 sorted by customer_last_name, then customer_first_ name. */
 --QUERY 2
-
-
-
-
+SELECT*
+FROM customer
+ORDER BY customer_last_name, customer_first_name
+LIMIT 10;
 --END QUERY
 
 
 --WHERE
 /* 1. Write a query that returns all customer purchases of product IDs 4 and 9. 
 Limit to 25 rows of output. */
-
-
+SELECT *
+FROM customer_purchases
+WHERE product_id IN (4,9)
+LIMIT 25;
 
 /*2. Write a query that returns all customer purchases and a new calculated column 'price' (quantity * cost_to_customer_per_qty), 
 filtered by customer IDs between 8 and 10 (inclusive) using either:
@@ -36,10 +36,11 @@ filtered by customer IDs between 8 and 10 (inclusive) using either:
 Limit to 25 rows of output.
 */
 --QUERY 3
-
-
-
-
+SELECT *
+,quantity * cost_to_customer_per_qty AS price
+FROM customer_purchases
+WHERE customer_id BETWEEN 8 AND 10
+LIMIT 25;
 --END QUERY
 
 
@@ -49,47 +50,60 @@ Using the product table, write a query that outputs the product_id and product_n
 columns and add a column called prod_qty_type_condensed that displays the word “unit” 
 if the product_qty_type is “unit,” and otherwise displays the word “bulk.” */
 --QUERY 4
-
-
-
-
+SELECT 
+    product_id,
+    product_name,
+    CASE 
+        WHEN product_qty_type = 'unit' THEN 'unit'
+        ELSE 'bulk'
+    END AS prod_qty_type_condensed
+FROM product;
 --END QUERY
 
 
 /* 2. We want to flag all of the different types of pepper products that are sold at the market. 
 add a column to the previous query called pepper_flag that outputs a 1 if the product_name 
 contains the word “pepper” (regardless of capitalization), and otherwise outputs 0. */
 --QUERY 5
-
-
-
-
+SELECT 
+    product_id,
+    product_name,
+    CASE 
+        WHEN product_qty_type = 'unit' THEN 'unit'
+        ELSE 'bulk'
+    END AS prod_qty_type_condensed,
+    CASE 
+        WHEN LOWER(product_name) LIKE '%pepper%' THEN 1
+        ELSE 0
+    END AS pepper_flag
+FROM product;
 --END QUERY
 
-
 --JOIN
 /* 1. Write a query that INNER JOINs the vendor table to the vendor_booth_assignments table on the 
 vendor_id field they both have in common, and sorts the result by market_date, then vendor_name.
 Limit to 24 rows of output. */
 --QUERY 6
-
-
-
-
+SELECT *
+FROM vendor v
+INNER JOIN vendor_booth_assignments vba
+    ON v.vendor_id = vba.vendor_id
+ORDER BY vba.market_date, v.vendor_name
+LIMIT 24;
 --END QUERY
 
 
-
 /* SECTION 3 */
 
 -- AGGREGATE
 /* 1. Write a query that determines how many times each vendor has rented a booth 
 at the farmer’s market by counting the vendor booth assignments per vendor_id. */
 --QUERY 7
-
-
-
-
+SELECT 
+    vendor_id,
+    COUNT(*) AS booth_count
+FROM vendor_booth_assignments
+GROUP BY vendor_id;
 --END QUERY
 
 
@@ -99,13 +113,24 @@ of customers for them to give stickers to, sorted by last name, then first name.
 
 HINT: This query requires you to join two tables, use an aggregate function, and use the HAVING keyword. */
 --QUERY 8
-
-
-
-
+SELECT
+    c.customer_id,
+    c.customer_first_name,
+    c.customer_last_name,
+    SUM(cp.quantity * cp.cost_to_customer_per_qty) AS total_spent
+FROM customer c
+INNER JOIN customer_purchases cp
+    ON c.customer_id = cp.customer_id
+GROUP BY
+    c.customer_id,
+    c.customer_first_name,
+    c.customer_last_name
+HAVING SUM(cp.quantity * cp.cost_to_customer_per_qty) > 2000
+ORDER BY c.customer_last_name, c.customer_first_name;
 --END QUERY
 
 
+
 --Temp Table
 /* 1. Insert the original vendor table into a temp.new_vendor and then add a 10th vendor: 
 Thomass Superfood Store, a Fresh Focused store, owned by Thomas Rosenthal
@@ -118,10 +143,24 @@ When inserting the new vendor, you need to appropriately align the columns to be
 VALUES(col1,col2,col3,col4,col5) 
 */
 --QUERY 9
-
-
-
-
+CREATE TEMP TABLE new_vendor AS
+SELECT *
+FROM vendor;
+
+INSERT INTO new_vendor (
+    vendor_id,
+    vendor_name,
+    vendor_type,
+    vendor_owner_first_name,
+    vendor_owner_last_name
+)
+VALUES (
+    10,
+    'Thomass Superfood Store',
+    'Fresh Focused',
+    'Thomas',
+    'Rosenthal'
+);
 --END QUERY
 
 
@@ -132,10 +171,12 @@ HINT: you might need to search for strfrtime modifers sqlite on the web to know
 and year are! 
 Limit to 25 rows of output. */
 --QUERY 10
-
-
-
-
+SELECT
+    customer_id,
+    STRFTIME('%m', market_date) AS month,
+    STRFTIME('%Y', market_date) AS year
+FROM customer_purchases
+LIMIT 25;
 --END QUERY
 
 
@@ -146,8 +187,13 @@ HINTS: you will need to AGGREGATE, GROUP BY, and filter...
 but remember, STRFTIME returns a STRING for your WHERE statement...
 AND be sure you remove the LIMIT from the previous query before aggregating!! */
 --QUERY 11
+SELECT
+    customer_id,
+    SUM(quantity * cost_to_customer_per_qty) AS total_spent
+FROM customer_purchases
+WHERE STRFTIME('%m', market_date) = '04'
+  AND STRFTIME('%Y', market_date) = '2022'
+GROUP BY customer_id;
+--END QUERY
 
 
-
-
---END QUERY