diff --git a/02_activities/assignments/DC_Cohort/Assignment1.md b/02_activities/assignments/DC_Cohort/Assignment1.md
index f650c9752..662972018 100644
--- a/02_activities/assignments/DC_Cohort/Assignment1.md
+++ b/02_activities/assignments/DC_Cohort/Assignment1.md
@@ -208,6 +208,8 @@ Link if you encounter a paywall: https://archive.is/srKHV or https://web.archive
 Consider, for example, concepts of fariness, inequality, social structures, marginalization, intersection of technology and society, etc.
 
 
-```
-Your thoughts...
+Data systems at first glance are viewed as objective platforms that organize information in a systematic manner. It is this very flawed perception that the article by Qadri, 2021 addresses, underscoring how these systems can be biased through social and cultural values. Using Pakistan’s ID system as an example, the author highlighted how the database makes assumptions about the martial status of those residing in the country. The national ID system considers that every individual should have two married parents which is a limited and narrow view of family.  What exacerbates this systematic bias is that individuals who do not fit within this rigid definition are hurdled with barriers that exclude them. This is a prime instance of how databases, while outwardly seen as positive and beneficial tools for data organization, can promulgate societal norms. 
+In day-to-day life, these types of limitations in multiple systems are present. It was only amid my undergraduate studies, where educational platforms (ACORN) began recognizing gender beyond the conventional binary options, and critically, provided categories of “wish not to disclose” as a reflection of respect for one’s privacy and autonomy to share information. Indeed, I acknowledge that these systems simplify data organization, however, in parallel, I also recognize that these tools of organization can easily overlook the complexities that compose human experiences, views and perspectives. The main question arising from these paucities is, how can these embedded values contribute to boarder inequalities? To answer this, when databases are modeled to reflect dominant social norms, then these databases or record management systems become a channel through which marginalized populations are inaccurately recorded, ultimately having large scale consequences such as access to services, policy decisions and allocation of resources. 
+Overall, considering the article, it is critical to deliberately and consciously consider how data systems can be designed to foster inclusivity, diversity and equity. In the today times, where data plays a critical role in major decisions, we must carefully evaluate how and which societal norms are defining these systems and whether they may be perpetuating marginalization further. 
+
 ```
diff --git a/02_activities/assignments/DC_Cohort/Diagram Assignment 1 SQL.png b/02_activities/assignments/DC_Cohort/Diagram Assignment 1 SQL.png
new file mode 100644
index 000000000..880e75529
Binary files /dev/null and b/02_activities/assignments/DC_Cohort/Diagram Assignment 1 SQL.png differ
diff --git a/02_activities/assignments/DC_Cohort/assignment1.sql b/02_activities/assignments/DC_Cohort/assignment1.sql
index 2ec561e2a..8a5cc8933 100644
--- a/02_activities/assignments/DC_Cohort/assignment1.sql
+++ b/02_activities/assignments/DC_Cohort/assignment1.sql
@@ -7,7 +7,8 @@
 /* 1. Write a query that returns everything in the customer table. */
 --QUERY 1
 
-
+SELECT *
+FROM customer;
 
 
 --END QUERY
@@ -17,6 +18,10 @@
 sorted by customer_last_name, then customer_first_ name. */
 --QUERY 2
 
+SELECT *
+FROM customer
+ORDER BY customer_last_name, customer_first_name
+LIMIT 10;
 
 
 
@@ -28,6 +33,11 @@ sorted by customer_last_name, then customer_first_ name. */
 Limit to 25 rows of output. */
 --QUERY 3
 
+SELECT *
+FROM customer_purchases
+WHERE product_id IN (4,9)
+LIMIT 25;
+
 
 
 
@@ -43,7 +53,10 @@ Limit to 25 rows of output.
 */
 --QUERY 4
 
-
+SELECT *, quantity * cost_to_customer_per_qty AS price
+FROM customer_purchases
+WHERE customer_id BETWEEN 8 AND 10
+LIMIT 25;
 
 
 --END QUERY
@@ -56,7 +69,14 @@ columns and add a column called prod_qty_type_condensed that displays the word 
 if the product_qty_type is “unit,” and otherwise displays the word “bulk.” */
 --QUERY 5
 
-
+SELECT 
+	product_id, 
+	product_name, 
+	CASE
+				WHEN product_qty_type = 'unit' THEN 'unit'
+				ELSE 'bulk'
+	END AS product_qty_type_condensed
+FROM product; 
 
 
 --END QUERY
@@ -67,7 +87,18 @@ add a column to the previous query called pepper_flag that outputs a 1 if the pr
 contains the word “pepper” (regardless of capitalization), and otherwise outputs 0. */
 --QUERY 6
 
-
+SELECT
+			product_id, 
+			product_name, 
+			CASE
+						WHEN product_qty_type = 'unit' THEN 'unit'
+						ELSE 'bulk'
+			END AS product_qty_type_condensed, 
+			CASE 
+						WHEN LOWER(product_name) LIKE '%pepper%' THEN 1
+						ELSE 0
+			END AS pepper_flag
+FROM product;
 
 
 --END QUERY
@@ -79,6 +110,13 @@ vendor_id field they both have in common, and sorts the result by market_date, t
 Limit to 24 rows of output. */
 --QUERY 7
 
+SELECT * 
+FROM vendor
+INNER JOIN vendor_booth_assignments
+			ON vendor.vendor_id = vendor_booth_assignments.vendor_id
+ORDER BY market_date, vendor_name
+LIMIT 24;
+
 
 
 
@@ -93,6 +131,10 @@ Limit to 24 rows of output. */
 at the farmer’s market by counting the vendor booth assignments per vendor_id. */
 --QUERY 8
 
+SELECT vendor_id, 
+				  COUNT(*) AS booth_rental_count
+FROM vendor_booth_assignments
+GROUP BY vendor_id;
 
 
 
@@ -105,7 +147,22 @@ 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 9
+SELECT
+			customer.customer_id,
+			customer.customer_first_name,
+			customer.customer_last_name, 
+			SUM(customer_purchases.quantity * customer_purchases.cost_to_customer_per_qty) AS total_spent
+FROM customer 
+INNER JOIN customer_purchases
+			ON customer.customer_id = customer_purchases.customer_id
+GROUP BY
+			customer.customer_id, 
+			customer.customer_first_name, 
+			customer.customer_last_name
+HAVING SUM(customer_purchases.quantity * customer_purchases.cost_to_customer_per_qty) > 2000 
+ORDER BY customer.customer_last_name, customer.customer_first_name;
 
+			
 
 
 
@@ -125,6 +182,21 @@ VALUES(col1,col2,col3,col4,col5)
 */
 --QUERY 10
 
+DROP TABLE IF EXISTS new_vendor;
+
+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'); 
+
 
 
 
@@ -139,6 +211,13 @@ and year are!
 Limit to 25 rows of output. */
 --QUERY 11
 
+SELECT
+			customer_id, 
+			strftime('%m', market_date) AS month, 
+			strftime('%y', market_date) AS year
+FROM customer_purchases
+LIMIT 25;
+			
 
 
 
@@ -153,7 +232,13 @@ but remember, STRFTIME returns a STRING for your WHERE statement...
 AND be sure you remove the LIMIT from the previous query before aggregating!! */
 --QUERY 12
 
-
+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