update exercises for clarity

exercises/00-setup.md

@@ -29,7 +29,7 @@ $ postgres=#
 ## Create Tables
 ```sql
 create table users (
-user_handle int Primary key,
+user_handle uuid Primary key,
 first_name text,
 last_name text,
 email text,
@@ -41,14 +41,14 @@ language text
 ```sql
 create table purchases (
 date date,
-user_handle int,
-sku int,
+user_handle uuid,
+sku uuid,
 quantity int
 );
 ```
 ```sql
 create table products (
-sku int,
+sku uuid,
 product text,
 price money
 );

exercises/01-import-data.md

@@ -2,4 +2,8 @@
 
 ## 01.
 
-Your goal is to bulk import CSV data into the users, purchases, and products tables. You will have to use the method shown in https://egghead.io/lessons/postgresql-bulk-insert-and-export-data-with-csv-files to complete this exercise.
+Your goal is to bulk import CSV data into the users, purchases, and products tables. 
+
+You will find `[product-data.csv](./product-data.csv)`, `[purchases-data.csv](./purchases-data.csv)`, and `[user-data.csv](./user-data.csv)` in this exercise folder that you can use to import into the `users`, `purchases`, and `products` tables. 
+
+You will have to use the method shown in https://egghead.io/lessons/postgresql-bulk-insert-and-export-data-with-csv-files to complete this exercise.

exercises/02-cast-int-to-string.md

@@ -2,4 +2,6 @@
 
 ## 01.
 
+Often times when working with data, you'll have the right data but in the wrong format that you need for the task at hand. You'll need to learn how to convert from one datatype to another.
+
 Your goal is to cast an integer into a string. Use both the long and shorthand methods of casting types. You will have to research the correct syntax yourself in order to complete this exercise.

exercises/05-CTE.md

@@ -15,4 +15,4 @@ group by user_handle, sku;
 
 ## 02. 
 
-Your goal is to find the average quantity a single user is purchasing of each product. You will need to use the CTE that you defined in Part 1 to do so.
+Your goal is to find the average quantity a single user is purchasing of each product instead of all of the users. You will need to re-use the CTE that you defined in Part 1 to do so.

exercises/06-filter-data.md

@@ -4,5 +4,5 @@
 Your goal is to return all female users in their 20's that have purchased more than 100 products. You will need to filter aggregate and row data.
 
 ## 02.
-What other ways can you filter this data?
-How could find demographic purchases the most of a single product?
+
+The team wants you to do market research on a product. How could find which demographic purchases the most of a single product? (e.g. 18302880 | Pepper - Pablano | \$5.28)

exercises/07-transactions.md

@@ -8,7 +8,7 @@ $ drop table users;
 
 ```sql
 $ create table users (
-user_handle int Primary key,
+user_handle uuid Primary key,
 first_name text,
 last_name text,
 email text,
@@ -27,7 +27,7 @@ insert into users values ('1', 'Agustin', 'Gillingham', '[email protected]
 Your goal is to guarantee that a payment is successfully processed. To do so, you will need to initiate a transaction that:
  - checks if product is available
  - inserts payment info into users table
- - adds item to purchases table
+ - adds items to purchases table
 
  If any of these actions fail, the transaction should be aborted.
 

exercises/purchases-data.csv

@@ -1,4 +1,4 @@
-date,id,sku,quantity
+date,user_handle,sku,quantity
 11/8/2019,79,18302861,6
 3/30/2020,51,18302862,1
 7/11/2019,75,18302863,3

exercises/solutions/06-filter-data.md

@@ -1,3 +1,4 @@
+## 01
 ```sql
 SELECT 
   u.user_handle, 
@@ -28,4 +29,13 @@ user_handle | sum
            2 | 146
           36 | 126
           93 | 110
+```
+
+## 02
+```sql
+postgres=# select email, users.user_handle, age, gender, sum(quantity) as total from users join purchases on (users.user_handle = purchases.user_handle) where sku=18302880 group by users.user_handle;
+       email          | user_handle | age | gender | total
+------------------------<del>-------------</del>-----<del>--------</del>--&#x2013;&#x2014;
+[email protected] | 16 | 19 | Male | 12
+(1 row)
 ```

exercises/user-data.csv

@@ -1,4 +1,4 @@
-id,first_name,last_name,email,gender,age,language
+user_handle,first_name,last_name,email,gender,age,language
 1,Ophelia,Claffey,[email protected],Female,40,Macedonian
 2,Marta,Brokenbrow,[email protected],Female,23,Somali
 3,Barney,Grenshields,[email protected],Male,66,Thai