{"action":"opened","issue":{"url":"https://api.github.com/repos/dellziam/sql-scratch-capstone-turn-in/issues/1","repository_url":"https://api.github.com/repos/dellziam/sql-scratch-capstone-turn-in","labels_url":"https://api.github.com/repos/dellziam/sql-scratch-capstone-turn-in/issues/1/labels{/name}","comments_url":"https://api.github.com/repos/dellziam/sql-scratch-capstone-turn-in/issues/1/comments","events_url":"https://api.github.com/repos/dellziam/sql-scratch-capstone-turn-in/issues/1/events","html_url":"https://github.com/dellziam/sql-scratch-capstone-turn-in/issues/1","id":334969995,"node_id":"MDU6SXNzdWUzMzQ5Njk5OTU=","number":1,"title":"Summary","user":{"login":"karl-project-review","id":37846313,"node_id":"MDQ6VXNlcjM3ODQ2MzEz","avatar_url":"https://avatars0.githubusercontent.com/u/37846313?v=4","gravatar_id":"","url":"https://api.github.com/users/karl-project-review","html_url":"https://github.com/karl-project-review","followers_url":"https://api.github.com/users/karl-project-review/followers","following_url":"https://api.github.com/users/karl-project-review/following{/other_user}","gists_url":"https://api.github.com/users/karl-project-review/gists{/gist_id}","starred_url":"https://api.github.com/users/karl-project-review/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/karl-project-review/subscriptions","organizations_url":"https://api.github.com/users/karl-project-review/orgs","repos_url":"https://api.github.com/users/karl-project-review/repos","events_url":"https://api.github.com/users/karl-project-review/events{/privacy}","received_events_url":"https://api.github.com/users/karl-project-review/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-06-22T18:05:45Z","updated_at":"2018-06-22T18:05:45Z","closed_at":null,"author_association":"NONE","body":"## Rubric Score\r\n### Criteria 1: Report: Are conclusions clear and supported by evidence in all eight answers?\r\n* _Score Level:_ 3/4 (Meets Expectations) \r\n* _Comment(s):_ You included support for all of your conclusions -- well done! However, in Step 3, the '% user' column in the table seems to represent the number of users who answered the question in the first row (ie 100% answered question 1), but in the subsequent rows it contains the number of users who dropped out after each question. Make sure each column in consistent with what sort of data it contains. Also, try to use more descriptive column names, as this will make it clearer what the table is showing. Also, in Step 6, the meaning of the is_purchase column in the table is ambiguous in this context, as it is listed as False for one group of aggregates and True for another. Thus, in its current form, this table's meaning is ambiguous and thus it doesn't adequately support the conclusions drawn from it. A potential way of improving this table in provided under Criteria 2 below.  \r\n### Criteria 2: Query Accuracy: Do queries do what they were supposed to do?\r\n* _Score Level:_ 3/4 (Meets Expectations)\r\n* _Comment(s):_ Your queries for step 1-5 all do what they are supposed to -- nice work! However, for step 6, it looks like the goal of the final query is to show the breakdown of how many customers who received 3 or 5 pairs of glasses actually made a purchase. However, since the counts of user_ids are only grouped by number_of_pairs, it is ambiguous how many people in each category actually made a purchase and what the is_purchase column means in this case. If we also grouped by is_purchase in addition to number_of_pairs,  then there would be a breakdown of how many users in each category either did or did not make a purchase, which should be more informative. We always need to be careful to make sure our queries break down the data in the manner that we want and that all of the columns we select still make sense in an aggregate like this.\r\n### Criteria 3: Query Formatting\r\n* _Score Level:_ 2/4 (Approaches Expectations)\r\n* _Comment(s):_ You did a good job of putting the different parts of queries (SELECTs, FROMs, WHEREs, etc) on their own lines and you generally give each column being selected its own line. However, the reserved keywords (SELECT, FROM, etc) should be in all caps, the SELECT lines should be at the same indentation level as the FROM and LEFT JOIN statements inside the WITH statement, the ON statements should be indented one level further than the JOIN statements, and there were places where the columns being selected were listed on the same line instead of being split up. Striving for more consistency in apply the SQL formatting guidelines will be helpful in making your code easy to read. \r\n### Criteria 4: Understanding underlying concepts and terminology\r\n* _Score Level:_ 3/4 (Meets Expectations)\r\n* _Comment(s):_ The relevant terminology is used appropriately. To take this project to the next level, though, consider discussing the funnel and the insights we can draw from it more in Step 6.\r\n\r\n### Overall Score: 11/16\r\nGood work! You successfully wrote most of the queries and provided some useful insight into the data. To take this project to the next level, try to rewrite the query mentioned in Step 6, and possibly do some additional analysis to see what insight we can draw from the funnel. Also, be sure to double check that all SQL queries used are consistent with proper SQL formatting.\r\n"}}
{"actor":{"display_login":"karl-project-review"}}