This case involves a Database creation for a Web-based music store called "Virtual Songs Ltd." that sells music Discs over the Internet. Virtual Songs Ltd. wants to keep information about their customers like: customer number, last name, first name, date of birth, street address, city, state (province), zip (postal code), phone and email address. Each customer may order many orders (or even none if prospective client) and each order will contain: order number, order date and order total. Order must exist for only one customer. Customers will always pay for their order with the credit card, so information about it is stored in the dependent (on Order) listing called "Payment". It will contain: card number, name on card, expiry date and card type (like Visa, Master, American-Express etc.). Order must be paid with the credit card before on-line transaction is saved and it has to be for at least one Disc. Every payment corresponds to an order and an order may contain multiple lines i.e., Discs. There is listing of all Discs called "Recording" and it is explained through: recording id, title, performer's name, selling (or current) price and quantity in stock. Each Disc belongs to a certain type or category of music like R&B, Jazz, Metal Rock, Alt Rock, Easy Rock, Classic Rock, Hip-Hop etc. and this will be stored in a look-up listing with category id and category description. Also, each Disc is produced by a certain music label (company) like Sony, Columbia, Virgin etc. and it is explained through: label id, label name and its URL site. You should assume that there may exist a brand new category of music so that no Disc is of that type yet, but for the label you will assume it can not be without any Disc in the catalog. Each order line will contain information about the actual price and quantity ordered. This price is a historical price of a Disc at the time of being sold to the customer. For example, Disc called "Eyes Open" by "Snow Patrol" may have cost $14 in September, but in November it may have cost $16 and for the Christmas sale only $12. The latest actual price is then equaled to the selling price in the "Recording" listing (this will be done through an Update Trigger in the Application code). So, selling or current price is always the most current price of the Disc. Music store also wants to track a history of price changes for any Disc, so that dependent listing "Recording History" needs to be created where each Disc can be tracked by price number (like 1, 2, 3 etc.) its old price (like $14, $16, $12) and the start date of each price like (09-SEP-06, 02-NOV-06 and 10-DEC-06). "Virtual Tunes Ltd." manages its Disc stock purchase by dealing with label's sales reps. Each label will have one or more sales reps and they are tracked by: rep number, last name, first name, phone number and email address. Each sales rep has divided its territory in regions, where they keep info only about region id and region name (like US-North, US-West, Canada, Europe, Asia etc.) It is possible that same region is covered with none or more than one sales rep. Note: Create meaningful names for all attributes and use # symbol for PK and (FK) for FK. Include ALL attributes for each entity incl. composite PK and every FK. Complete ERD should be in 2NF and must contain cardinality ratios and clear relationship notations. Part 2 DDL/DML script Using the Songs ERD, you need to provide SQL scripts with DDL/DML statements that will implement a Physical Solution for that Database Scenario as: DDL scripts for creation of all Tables from the ERD. Adding all PK, FK, UK and CK Constraints needed for these tables either with CREATE TABLE (UK, CK) or later with ALTER TABLE statements (PK, FK) DML scripts to insert for at least five rows of sample data for each table 1. 2. 3. Check constraints you must implement: Order Total in table ORDERS must be a positive number CardType in table PAYMENT must belong to the set of values (VISA, MAST, AMEX) CategoryDesc must belong to the set of values ('R&B', 'Jazz', 'Metal Rock", 'Alt Rock', 'Easy Rock', 'Classic Rock', 'Hip-Hop'} Qty in table ORDER_LINE must be non-negative integer number ActPrice in table ORDER_LINE must be greater than zero Price in table RECORD HIST must be positive decimal number not greater than $999.99 You must add not null constraints as you see fit. Unique constraints (Not shown in ERD): Email in table CUSTOMER Email in table SALES REP Part 3 Stored Procedure Write a procedure named Recording Selling Price Report to show the number of recordings in each price category as follows: If selling price is less than the average selling price then the category is LOW Else the category is HIGH The stored procedure must print how many of LOW and HIGH recordings are available in the database. Part 4 NoSQL You need to identify the collections you need in this part and display sample json data inside them. For example, the Customer collection could contain {"_id":1,"LastName":"Alam", "FirstName":"Tanvir","DoB":"1/1/2000","Email":"Tanvir.alam@senecacollege.ca ","phone":"800-800-8080", "Zip":"AIAIAI"} etc. You must use all the sample data you used in Part 2. You need to research how to handle 1-M relationship in NoSQL to display in your sample data design. One inefficient way is to follow the ERD. You may set up the collections and insert data into your laptop mongoDB installation or you may set them up in Atlas free tier cluster. If you use mongosh. then provide screenshots of the insert statements (successful insert). If you use compass or atlas GUI, provide screenshots of the collection documents. Activate Windows Go to Settings to activate Windows