MIS 331 MusicMash Final Report

December 10, 2015

Kyndall Jonhston | kyndalljohnston@email.arizona.edu Tyler Bauer | tylerbauer@email.arizona.edu

Joseph Khoury | josephkhoury@email.arizona.edu Douglas Izzo | douglasizzo@arizona.edu

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Table of Contents Introduction ............................................................................................................... 3 Questions When Building the Database ............................................................... 4 Assumptions .............................................................................................................. 4 ER Diagram: Preliminary .......................................................................................... 5 ER Diagram: Implementation ................................................................................. 6 Normalized Relations ............................................................................................... 7 Referential Integrity Constraints .......................................................................... 10 Indexes ....................................................................................................................... 11 Denormalization Decisions ..................................................................................... 11 SQL Code Used to Build Database ....................................................................... 12

Defining the Database: SQL Statements ..................................................................... 12 Populating the Database with Sample Data: Insert Statements .............................. 16

Implemented Database Structure ........................................................................ 35 Properties of Fields of Tables in Implemented Database ............................... 36 Queries ..................................................................................................................... 39 User Documentation of Database ........................................................................ 43 Training and Use of Database .............................................................................. 45 Technology Issues .................................................................................................. 46 Lessons Learned ..................................................................................................... 47

Introduction In order to provide our client MusicMash with a proper database system we incorporated multiple stages within our design. Below is the operational view of our database by which the MusicMash employee will view upon login. This paper will then outline the steps in order to come the proposed scenario as well as provide insight on lessons learned throughout the project.

Questions When Building the Database In starting out, we proposed a series of questions to MusicMash as it pertained to building the database.

1. Do people have the ability to purchase songs after their prescription runs out?

a. No 2. Is data about a customer that has an expired membership kept after the

membership expired? a. Yes

3. Is the company going to update its management system after 10 years? a. Yes

4. d. How many songs will be in the database at one time? a. 100,000,000

5. e. Is customer name necessary to Music Mash besides credit card information?

a. Yes Assumptions Next, we created an ER Diagram to serve as the foundation in building the database. Assumptions were made in building the database for MusicMash. Please reference the assumptions to follow for our ER Diagrams and Relational Model. Assumptions are denoted by a (*) in the ER diagrams. *1 Assume CUSTOMER rates at least one SONG *2 Assume SONG is rated by at least one CUSTOMER *3 Assume CUSTOMER does not have to purchase ALBUM *4 Assume ALBUM does not have to be purchased by CUSTOMER *5 Assume SONG has one and only one ARTIST *6 Assume ARTIST has at least one SONG *7 Assume SONG has one and only one RECORD LABEL *8 Assume RECORD LABEL has at least one SONG *9 Assume RECORD LABEL has one and only one ACCOUNT EXEC *10 Assume ACCOUNT EXEC has at least one RECORD LABEL *11 Assume ALBUM has one and only one ARTIST *12 Assume ARTIST has at least one ALBUM *13 Assume SONG has one and only one ALBUM *14 Assume CUSTOMER does not have to purchase SONG *15 Assume SONG does not have to be purchased by CUSTOMER *16 Assume CUSTOMER creates at least one STATION *17 Assume STATION is created by at least one CUSTOMER *18 Assume SONG belongs to at least one STATION *19 Assume STATION has at least one SONG *20 Assume ARTIST signs one and only one RECORD LABEL *21 Assume RECORD LABEL is signed by at least one ARTIST

ER Diagram: Preliminary

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ER Diagram: Implementation

Normalized Relations We needed to prepare our ER Diagram to be translated in to SQL code, which would then be implemented in our database management system. We defined each constraint and how it would be related to the relational attributes provide by the business scenario.

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Referential Integrity Constraints Before we inserted data in to our database, we needed to define the constraints to eliminate data redundancy, as well as form the primary keys. The foreign keys help ensure alignment of the tables.

A. Account Exec must have its own primary key of EID in order to keep track of each specific Executive.

B. Each Artist must have its own ArtID in order to keep track of each individual Artist.

C. The customer table must have a primary key denoting each indivdule customer of CID.

D. Each time a customer is contacted must be recorded with its own id of ConID. Customer data is recorded in the contact table meaning that the data must reference the customer table for each specific customer id CID.

E. Each individual song must have its own identification which requires a primary key of SongID. Since an Artist is associated with each song, a foreign key of ArtID is necessary. Another foreign key of RID will be needed to denote the specific record label assigned to the song.

F. The customer and song interaction must be recorded for each specific interaction between therefore needing a primary key of CustSong_ID. Since the customer is recorded in this interaction the foreign key CID must be taken from Customer for reference purposes. Also the song that is interacted with the customer must be recorded, therefore the use of SongID must be taken from Song.

G. The interaction of a customer purchasing a song must be recorded with the primary key of CSP_ID. Since the customer is recorded in this interaction the foreign key CID must be taken from Customer for reference purposes. Also the song that is interacted with the customer must be recorded, therefore the use of SongID must be taken from Song.

H. Albums must be recorded with the primary key of AlbID for each album and since artists go hand and hand with albums, the artist id of ArtID must be referenced from table Artist.

I. Customer’s can create stations which must be recorded by a primary key of CustStat_ID for every single station created. Since customer data is recorded a foreign key of CID must reference the customer table and the Album id must reference the Album table of ALBID.

J. The table that records data for non subscribers contains information regarding customers which means it must be cross referenced with the table for customer’s CID.

K. The Record Label table must have its own id denoting the recordlabel as a primary key called RID. This table will reference the account

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executives therefore it must have a foreign key of EID to denote the account executives by their id.

L. Each station created for songs must have its own StationId denoting the specific station.

M. The station song table captures which songs are in each station and have their own distinct code called Station_SongID. They will reference both the station and the song with the denotations of StationID and SongID respectively.

N. The subscription table denotes what type of subscription is selected by the primary key of SuselectID.

O. The subscriber table must pull together information from the customer tables CID to denote the customer and must also the subscription type from the table subscription as SubselectID.

P. Each customer’s interaction with an album must be recorded by the primary key of Cust_ALb. This table must draw from the AlbID as well as the CID from the Album and Customer table respectively.

Indexes We need a four-pronged index for songrating, songtype, songratingtime, and songskiptimes. We need this index so we can calculate the main algorithm MusicMash is looking for us to solve. Our main problem is that we need to find whether customers like certain songs in the day or at night and certain types of song. This composite index meets that requirement. The usage frequency index was created because the case asked us how often songs are played. The loyalty of subscribers index is necessary because MusicMash wants to identify loyal customers to give them discounts. Denormalization Decisions We have decided not to denomalize any tables because all of our tables contain useful data. We have made the minimum amount of tables required to solve this case under our desire and we want to keep the data as crisp and clean for the user as possible. One potential denormalization is the subscriber and non-subscriber tables but we decided against it because subscriber has a relationship with subscription. If we denormalized subscriber and non-subscriber, we would have a lot of unnecessary null values. We believe we provide a strong database that does not need to be denormalized. It is efficient in search with the indexes and because we used so few indexes there's no need to denormalize the tables for searchability purposes. Our strong index design that aligns with customer needs also allows us to keep the tables the way they are and if we denormalized those tables we may need to get rid of some of those indexes. The current design is the most user friendly possible because if we were MusicMash we would want these indexes for search and because the database has common sense to it.

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SQL Code Used to Build Database Defining the Database: SQL Statements The CREATE TABLE and INSERT statements were needed to create the tables in our database. The INSERT statements are sample data that we introduced to our database by way of SQL code. ACCOUNTEXC TABLE CREATE TABLE ACCOUNTEXEC ( EId VARCHAR2(3) Not NULL, EName VARCHAR2(20), CONSTRAINT ACCOUNTEXEC_PK PRIMARY KEY (EId) ); ALBUM TABLE CREATE TABLE ALBUM ( AlbID VARCHAR2(7) NOT NULL, ArtID VARCHAR2(10) NOT NULL, AlbCost NUMBER(5,2), Albname VARCHAR2(25), Genre VARCHAR2(10), CONSTRAINT ALBUM_PK PRIMARY KEY (AlbID), CONSTRAINT ALBUM_FK FOREIGN KEY (ArtID) REFERENCES ARTIST ); ARTIST TABLE CREATE TABLE ARTIST ( ArtID VARCHAR2(10), ArtName VARCHAR2(30), CONSTRAINT ARTIST_PK PRIMARY KEY (ArtID) ); CONTACT TABLE CREATE TABLE CONTACT ( CId VARCHAR2(10) NOT NULL, ConID VARCHAR2(10) NOT NULL, Ctype VARCHAR2(20), Notification VARCHAR2(20), CONSTRAINT CONTACT_PK PRIMARY KEY (ConID), CONSTRAINT CONTACT_FK FOREIGN KEY (CId) REFERENCES CUSTOMER(CId) ); CUSTOMER TABLE

CREATE TABLE CUSTOMER (

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CId VARCHAR2(10) NOT NULL, CType VARCHAR2(2) NOT NULL, CStreet VARCHAR2(58), CState VARCHAR2(14), CZip VARCHAR2(10), CCity VARCHAR2(44), CSignupDate DATE, CSignupTime TIMESTAMP, CDob DATE, CEmail VARCHAR2(100), CNAME VARCHAR2(30), CGENDER VARCHAR2(2), CONSTRAINT CUSTOMER_PK PRIMARY KEY (CID) ); CUSTOMER_ALBUM TABLE CREATE TABLE CUSTOMER_ALBUM ( CUST_ALB VARCHAR2(7), CID VARCHAR2(10), ALBID VARCHAR2(7), PURCHASEALBUMTIME DATE, CONSTRAINT CUSTOMER_ALBUM_PK PRIMARY KEY (CUST_ALB), CONSTRAINT CUSTOMER_ALBUM_FK1 FOREIGN KEY (CId) REFERENCES CUSTOMER, CONSTRAINT CUSTOMER_ALBUM_FK2 FOREIGN KEY (ALBID) REFERENCES ALBUM ); CUSTOMER_SONG TABLE CREATE TABLE CUSTOMER_SONG ( CustSong_ID VARCHAR2(7) NOT NULL, CId VARCHAR2(10) NOT NULL, SongId VARCHAR2(7) NOT NULL, SongRating VARCHAR2(2), SongRatingTime TIMESTAMP NOT NULL, SongType VARCHAR2(8), SongSkipTimes INTEGER, SongUsageFrequency NUMBER(3), ListeningTime TIMESTAMP, SkipTimeDate TIMESTAMP, CONSTRAINT CUSTOMER_SONG_PK PRIMARY KEY (CustSong_ID), CONSTRAINT CUSTOMER_SONG_FK1 FOREIGN KEY (CId) REFERENCES CUSTOMER, CONSTRAINT CUSTOMER_SONG_FK2 FOREIGN KEY (SongId) REFERENCES SONG ); CUSTOMER_SONGP TABLE CREATE TABLE CUSTOMER_SONGP ( CSP_ID VARCHAR2(17) NOT NULL, CId VARCHAR2(10) NOT NULL, SongId VARCHAR2(7) NOT NULL,

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Song_Price NUMBER (5,2), PurchaseTime TIMESTAMP, CONSTRAINT CUSTOMER_SONGP_PK PRIMARY KEY (CSP_ID), CONSTRAINT CUSTOMER_SONGP_FK1 FOREIGN KEY (CId) REFERENCES CUSTOMER, CONSTRAINT CUSTOMER_SONGP_FK2 FOREIGN KEY (SongId) REFERENCES SONG ); CUSTOMER_STATION TABLE CREATE TABLE CUSTOMER_STATION ( CustStat_ID VARCHAR2(5) NOT NULL, CId VARCHAR2(10) NOT NULL, ALBID VARCHAR2(7) NOT NULL, CreationSDate DATE, CONSTRAINT STATION_PK1 PRIMARY KEY (CustStat_ID), CONSTRAINT CUSTOMER_STATION_FK10 FOREIGN KEY (Cid) REFERENCES CUSTOMER, CONSTRAINT CUSTOMER_STATION_FK20 FOREIGN KEY (ALBID) REFERENCES ALBUM ); NON_SUBSCRIBER TABLE CREATE TABLE NON_SUBSCRIBER ( CID VARCHAR2(10) NOT NULL, NSDuration VARCHAR2(5), NSStartTime TIMESTAMP, NSendTime TIMESTAMP, CONSTRAINT NON_SUBSCRIBER_FK FOREIGN KEY (CId) REFERENCES CUSTOMER ); RECORDLABEL TABLE CREATE TABLE RECORDLABEL ( RId VARCHAR2(3) NOT NULL, EId VARCHAR2(3) NOT NULL, RecName VARCHAR2(20), ProfitRatio NUMBER(5,1), CONSTRAINT RECORDLABEL_PK PRIMARY KEY (Rid), CONSTRAINT RECORDLABEL_FK FOREIGN KEY (EId) REFERENCES ACCOUNTEXEC(EId) ); SONG TABLE CREATE TABLE SONG ( SongID VARCHAR2(7) NOT NULL, ArtID VARCHAR2(10) NOT NULL, RId VARCHAR2(3) NOT NULL, SName VARCHAR2(20), SGenre VARCHAR2(20), SArtist VARCHAR2(20),

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SReleaseDate DATE, CONSTRAINT SONG_PK PRIMARY KEY (SongID), CONSTRAINT SONG_FK1 FOREIGN KEY (ArtID) REFERENCES ARTIST, CONSTRAINT SONG_FK2 FOREIGN KEY (RId) REFERENCES RECORDLABEL ); STATION TABLE CREATE TABLE STATION ( StationID varchar2(5) NOT NULL, StartType varchar2(5), CONSTRAINT STATION_PK PRIMARY KEY (StationID) ); STATION_SONG TABLE

CREATE TABLE STATION_SONG ( STATSONGID VARCHAR2(10) NOT NULL, StationID VARCHAR2(5) NOT NULL, SongId VARCHAR2(7) NOT NULL, CONSTRAINT STATION_SONG_PK PRIMARY KEY (STATSONGID), CONSTRAINT STATION_SONG_FK1 FOREIGN KEY (StationId) REFERENCES STATION, CONSTRAINT STATION_SONG_FK2 FOREIGN KEY (SongId) REFERENCES SONG ); SUBSCRIBER TABLE CREATE TABLE SUBSCRIBER ( CId VARCHAR2(10) NOT NULL, SubselectID VARCHAR (6) NOT NULL, CCNumber NUMBER(16), CCExpMonth NUMBER(2), CCExpYear NUMBER(4), CCSecurityCode NUMBER(3), CCPaypalOption VARCHAR2(1), SDuration VARCHAR2(30), SendDate DATE, CONSTRAINT SUBSCRIBER_FK FOREIGN KEY (CId) REFERENCES CUSTOMER(CId), CONSTRAINT SUBSCRIBER_FK2 FOREIGN KEY (SubselectId) REFERENCES SUBSCRIPTION(SubselectId) ); SUBSCRIPTION TABLE CREATE TABLE SUBSCRIPTION ( SubselectId VARCHAR2(6) NOT NULL, SubscriptionType VARCHAR2(2), CONSTRAINT SUBSCRIPTION_PK PRIMARY KEY (SubselectId) );

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Indexes CREATE INDEX idx_MainAlg ON CUSTOMER_SONG(Songrating, Songtype, Songratingtime, Songskiptimes); CREATE INDEX idx_UsageFreq ON CUSTOMER_SONG(Songusagefrequency); CREATE INDEX idx_CustomerLoyalty ON SUBSCRIBER(SDuration); Populating the Database with Sample Data: Insert Statements ACCOUNTEXC TABLE INSERT INTO ACCOUNTEXEC VALUES ('001','Pulson Records'); INSERT INTO ACCOUNTEXEC VALUES ('002', 'Fly Records'); INSERT INTO ACCOUNTEXEC VALUES ('003','Yo Records'); INSERT INTO ACCOUNTEXEC VALUES ('004','Rap Records'); INSERT INTO ACCOUNTEXEC VALUES ('005','Crash Records'); INSERT INTO ACCOUNTEXEC VALUES ('006','Latin Records'); INSERT INTO ACCOUNTEXEC VALUES ('007','Titan Records'); INSERT INTO ACCOUNTEXEC VALUES ('008','Retoggle Records'); INSERT INTO ACCOUNTEXEC VALUES ('009','Gofish Records'); INSERT INTO ACCOUNTEXEC VALUES ('010','Bingo Records'); ALBUM TABLE INSERT INTO ALBUM VALUES ('0000001','0000000001',20.99,'TheComeback','Rock' ); INSERT INTO ALBUM VALUES ('0000002','0000000002',20.99,'TheReturn','Hip-Hop' ); INSERT INTO ALBUM VALUES ('0000003','0000000003',2.99,'Love','Latin' ); INSERT INTO ALBUM VALUES ('0000004','0000000004',0.99,'Loving','Latin' ); INSERT INTO ALBUM VALUES ('0000005','0000000005',30.99,'Adventure','Latin' ); INSERT INTO ALBUM VALUES ('0000006','0000000006',10.99,'Journey','Latin' ); INSERT INTO ALBUM VALUES ('0000007','0000000007',40.99,'Baby','Pop' ); INSERT INTO ALBUM VALUES ('0000008','0000000008',10.99,'Star','Pop' ); INSERT INTO ALBUM VALUES ('0000009','0000000009',30.99,'Yoyo','Rap'

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); INSERT INTO ALBUM VALUES ('0000010','0000000010',20.99,'Comingback','Rap' ); ARTIST TABLE INSERT INTO ARTIST VALUES ('0000000001','PlusBoys'); INSERT INTO ARTIST VALUES ('0000000002','Jerseyboys'); INSERT INTO ARTIST VALUES ('0000000003','Princeroyce'); INSERT INTO ARTIST VALUES ('0000000004','Nickyjam'); INSERT INTO ARTIST VALUES ('0000000005','EnriqueInglesias'); INSERT INTO ARTIST VALUES ('0000000006','Shakira'); INSERT INTO ARTIST VALUES ('0000000007','JustinBieber'); INSERT INTO ARTIST VALUES ('0000000008','SelenaGomez'); INSERT INTO ARTIST VALUES ('0000000009','LittleJ'); INSERT INTO ARTIST VALUES ('0000000010','Mr.P'); CONTACT TABLE INSERT INTO CONTACT VALUES ('0000000001','0000000001','Email','1 Week Reminder'); INSERT INTO CONTACT VALUES ('0000000003','0000000002','Email','1 Week Reminder'); INSERT INTO CONTACT VALUES ('0000000005','0000000003','Email','1 Week Reminder'); INSERT INTO CONTACT VALUES ('0000000007','0000000004','Email','1 Week Reminder'); INSERT INTO CONTACT VALUES ('0000000009','0000000005','Email','1 Week Reminder'); INSERT INTO CONTACT VALUES ('0000000011','0000000006','Email','1 Week Reminder'); INSERT INTO CONTACT VALUES ('0000000013','0000000007','Email','1 Week Reminder'); INSERT INTO CONTACT VALUES ('0000000015','0000000008','Email','1 Week Reminder'); INSERT INTO CONTACT VALUES ('0000000017','0000000009','Email','1 Week Reminder'); INSERT INTO CONTACT VALUES ('0000000019','0000000010','Email','1 Week Reminder'); CUSTOMER TABLE INSERT INTO CUSTOMER VALUES ( '0000000001', 'NS', 'Park', 'Arizona', '85719', 'Tucson', '24-Nov-2015', '24-Nov-2015 11:19:00AM', '22-Jun-1995',

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'FrankSinatra@gmail.com', ‘Frank Sinatra’, ‘M’ ); INSERT INTO CUSTOMER VALUES ( '0000000002', 'NS', 'Broadway', 'Arizona', '85028', 'Phoenix', '24-Nov-2015', '24-Nov-2015 11:19:00AM', '22-May-1975', 'peterthiel@paypal.com', ‘Peter Thiel’, ‘M’ ); INSERT INTO CUSTOMER VALUES ( '0000000003', 'NS', 'Rightfella', 'Alaska’, '30019', 'Anchorage', '14-Jan-2015', '14-Jan-2015 01:19:00AM', '02-Jun-1993', 'kingkong@gmail.com', ‘King Kong’, ‘F’ ); INSERT INTO CUSTOMER VALUES ( '0000000004', 'S', 'Mant', 'Florida’, '65028', 'Daytona', '26-Nov-2015', '26-Nov-2015 06:15:00AM', '10-Apr-1974', 'gregl@paypal.com', ‘Greg Lapiner’, ‘F’ ); INSERT INTO CUSTOMER VALUES ( '0000000005',

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'NS', 'Trench', 'New Mexico’, '17019', 'New Mexico', '20-Jan-2015', '20-Jan-2015 01:19:00AM', '15-Aug-1990', 'JustinBeebs@gmail.com', ‘Justin Beebs’, ‘M’ ); INSERT INTO CUSTOMER VALUES ( '0000000006', 'S', 'Broadway', 'New York’, '10001', 'New York', '03-Dec-2015', '03-Dec-2015 07:19:00PM', '03-Dec-1979', 'seanparker@napster.com', ‘Sean Parker’, ‘F’ ); INSERT INTO CUSTOMER VALUES ( '0000000007', 'NS', 'Alder', 'New York', '10701', 'Yonkers', '07-Aug-2015', '07-Aug-2015 03:59:00PM', '10-July-1993', 'DerickJeter@gmail.com', ‘Derick Jeter’, ‘M’ ); INSERT INTO CUSTOMER VALUES ( '0000000008', 'S', 'University Ave', 'New York', '10003', 'New York',

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'03-Nov-2015', '03-Nov-2015 05:19:00PM', '19-Mar-1982', 'Johnny@facebook.com', ‘Johnny Football’, ‘F’ ); INSERT INTO CUSTOMER VALUES ( '000000009', 'NS', 'Gitwell', 'Maine’, '10621', 'Albany', '17-Mar-2015', '17-Mar-2015 03:59:00PM', '10-Feb-1925', 'AbrahamLink@gmail.com', ‘Abraham Linkoln’, ‘M’ ); INSERT INTO CUSTOMER VALUES ( '0000000010', 'S', 'University Ave’', 'New York’, '10003', 'New York', '03-Nov-2015', '03-Nov-2015 05:19:00PM', '18-Mar-1982', 'eduardosaverin@facebook.com', ‘Eduardo Saver’, ‘M’ ); INSERT INTO CUSTOMER VALUES ( '0000000011', 'NS', 'Park', 'Arizona', '85719', 'Tucson', '07-Dec-2015', '07-Dec-2015 09:19:00AM', '22-May-1995', 'mattp@gmail.com', ‘Matt Presto’, ‘F’ );

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INSERT INTO CUSTOMER VALUES ( '0000000012', 'S', 'Park', 'Arizona', '85719', 'Tucson', '07-Nov-2015', '07-Nov-2015 09:19:00AM', '23-May-1995', 'johndoejr@email.arizona.edu', ‘John Doe’, ‘M’ ); INSERT INTO CUSTOMER VALUES ( '0000000013', 'NS', 'Park', 'Arizona', '85719', 'Tucson', '07-Nov-2015', '07-Nov-2015 09:19:00AM', '22-May-1995', 'lucasde@gmail.com', ‘Lucas De’, ‘M’ ); INSERT INTO CUSTOMER VALUES ( '0000000014', 'S', 'Park', 'Arizona', '85719', 'Tucson', '15-Nov-2015', '15-Nov-2015 09:19:00AM', 20, '25-May-1995', 'cynthiarae@email.arizona.edu', ‘Cynthia Rae’, ‘M’ ); INSERT INTO CUSTOMER VALUES ( '0000000015', 'NS', 'Park', 'Arizona',

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'85719', 'Tucson', '07-Oct-2015', '07-Oct-2015 09:19:00AM', 20, '22-May-1997', 'john@email.arizona.edu', ‘John Lam’, ‘F’ ); INSERT INTO CUSTOMER VALUES ( '0000000016', 'S', 'Park', 'Arizona', '85719', 'Tucson', '09-Nov-2015', '09-Nov-2015 09:19:00AM', 20, '09-Sep-1995', 'johnrichardsmith@email.arizona.edu' ‘John Richard’, ‘F’ ); INSERT INTO CUSTOMER VALUES ( '0000000017', 'NS', 'Park', 'Arizona', '85719', 'Tucson', '08-Oct-2015', '08-Oct-2015 09:19:00AM', '09-May-1997', 'kelsey@email.arizona.edu', ‘Kelsey Han’, ‘F’ ); INSERT INTO CUSTOMER VALUES ( '0000000018', 'S', 'Park', 'Arizona', '85719', 'Tucson', '20-Nov-2015', '20-Nov-2015 09:19:00AM', '10-Sep-1995',

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'ricardozavala@email.arizona.edu', ‘Ricardo Dozavala’, ‘F’ ); INSERT INTO CUSTOMER VALUES ( '0000000019', 'NS', 'Park', 'Arizona', '85715', 'Tucson', '15-Oct-2015', '15-Oct-2015 09:19:00AM', '20-May-1997', 'brittney@email.arizona.edu', ‘Brittney Spears’, ‘F’ ); INSERT INTO CUSTOMER VALUES ( '0000000020', 'S', 'Park', 'Arizona', '85719', 'Tucson', '20-Dec-2015', '20-Dec-2015 09:19:00AM', '10-Oct-1995', 'cristianoronaldo@email.arizona.edu', ‘Christiano Ronaldo’, ‘F’ ); CUSTOMER_SONG TABLE INSERT INTO CUSTOMER_SONG VALUES ('0000001','0000000001','0000001','10','22-Nov-2015 04:59:00PM','Mellow',1,23,'23-Nov-2015 03:10:00PM','10-Jan-2015 06:53:00AM'); INSERT INTO CUSTOMER_SONG VALUES ('0000002','0000000002','0000002','9','18-Dec-2015 04:59:00PM','Mellow',2,57,'13-Dec-2015 10:52:00PM','11-Feb-2015 06:23:00PM'); INSERT INTO CUSTOMER_SONG VALUES ('0000003','0000000003','0000003','8','21-Jan-2015 04:59:00PM','Fast',3,683,'03-Jan-2015 05:32:00AM','12-May-2015 08:53:00AM'); INSERT INTO CUSTOMER_SONG VALUES ('0000004','0000000004','0000004','7','23-Aug-2015

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04:59:00PM','Workout',4,1,'18-Aug-2015 08:02:00PM','13-Apr-2015 02:53:00AM'); INSERT INTO CUSTOMER_SONG VALUES ('0000005','0000000005','0000005','533','25-Jun-2015 04:59:00PM','Slowdown',5,23,'12-Jun-2015 12:02:00AM','14-Jan-2015 03:53:00PM'); INSERT INTO CUSTOMER_SONG VALUES ('0000006','0000000006','0000006','211','26-Feb-2015 04:59:00PM','Fast',6,23,'09-Feb-2015 05:02:00PM','15-Jan-2015 06:13:00AM'); INSERT INTO CUSTOMER_SONG VALUES ('0000007','0000000007','0000007','432','02-Jul-2015 04:59:00PM','Roadtrip',7,23,'11-Jul-2015 01:12:00AM','17-Jan-2015 02:53:00PM'); INSERT INTO CUSTOMER_SONG VALUES ('0000008','0000000008','0000008','18','03-Mar-2015 04:59:00PM','Relax',8,8,'28-Mar-2015 05:32:00PM','18-Mar-2015 01:53:00AM'); INSERT INTO CUSTOMER_SONG VALUES ('0000009','0000000009','0000009','8','04-May-2015 04:59:00PM','Sleepy',9,101,'26-May-2015 02:02:00AM','19-Feb-2015 02:27:00PM'); INSERT INTO CUSTOMER_SONG VALUES ('0000010','0000000010','0000010','5','05-Nov-2015 04:59:00PM','Mellow',10,23,'10-Nov-2015 02:02:00PM','20-Jan-2015 07:23:00AM'); CUSTOMER_SONGP TABLE INTO CUSTOMER_SONGP VALUES ( '00000000000000001', '0000000001', '0000001', 2.99, '30-Jun-2015 10:30:00PM' ); INSERT INTO CUSTOMER_SONGP VALUES ( '00000000000000002', '0000000002', '0000002', 1.99, '01-NOV-2015 10:50:00PM' ); INSERT INTO CUSTOMER_SONGP VALUES ( '00000000000000003', '0000000003', '0000003', 2.99, '04-OCT-2015 09:30:00AM'

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); INSERT INTO CUSTOMER_SONGP VALUES ( '00000000000000004', '0000000004', '0000004', 1.99, '14-JAN-2015 04:30:00PM' ); INSERT INTO CUSTOMER_SONGP VALUES ( '00000000000000005', '0000000005', '0000005', 2.99, '25-DEC-2015 02:00:00PM' ); INSERT INTO CUSTOMER_SONGP VALUES ( '00000000000000006', '0000000006', '0000006', 1.99, '08-AUG-2015 11:30:00AM' ); INSERT INTO CUSTOMER_SONGP VALUES ( '00000000000000007', '0000000007', '0000007', 0.99, '10-JUN-2015 01:30:00PM' ); INSERT INTO CUSTOMER_SONGP VALUES ( '00000000000000008', '0000000008', '0000008', 0.99, '01-MAY-2015 12:15:00PM' ); INSERT INTO CUSTOMER_SONGP VALUES ( '00000000000000009', '0000000009', '0000009', 1.99, '22-JUN-2015 08:15:00PM' ); INSERT INTO CUSTOMER_SONGP VALUES ( '00000000000000010',

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'0000000010', '0000010', 2.99, '14-FEB-2015 07:30:00PM' ); CUSTOMER_ALBUM TABLE INSERT INTO CUSTOMER_ALBUM VALUES ( '0000001', '0000000001', '0000001', '05-May-2015' ); INSERT INTO CUSTOMER_ALBUM VALUES ( '0000002', '0000000002', '0000002', '05-Dec-2016' ); INSERT INTO CUSTOMER_ALBUM VALUES ( '0000003', '0000000003', '0000003', '05-May-2017' ); INSERT INTO CUSTOMER_ALBUM VALUES ( '0000004', '0000000004', '0000004', '05-May-2018' ); INSERT INTO CUSTOMER_ALBUM VALUES ( '0000005', '0000000005', '0000005', '05-May-2016' ); INSERT INTO CUSTOMER_ALBUM VALUES ( '0000006', '0000000006', '0000006', '05-May-2017' ); INSERT INTO CUSTOMER_ALBUM VALUES (

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'0000007', '0000000007', '0000007', '05-May-2016' ); INSERT INTO CUSTOMER_ALBUM VALUES ( '0000008', '0000000008', '0000008', '05-May-2017' ); INSERT INTO CUSTOMER_ALBUM VALUES ( '0000009', '0000000009', '0000009', '05-May-2018' ); INSERT INTO CUSTOMER_ALBUM VALUES ( '0000010', '0000000010', '0000010', '05-May-2017' ); CUSTOMER_STATION TABLE INSERT INTO CUSTOMER_STATION VALUES ( '00001', '0000000001', '0000001', '24-Nov-2015' ); INSERT INTO CUSTOMER_STATION VALUES ( '00002', '0000000002', '0000002', '14-Dec-2015' ); INSERT INTO CUSTOMER_STATION VALUES ( '00003', '0000000003', '0000003', '10-Jan-2015' ); INSERT INTO CUSTOMER_STATION VALUES ( '00004',

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'0000000004', '0000004', '11-Jun-2015' ); INSERT INTO CUSTOMER_STATION VALUES ( '00005', '0000000005', '0000005', '02-Jul-2014' ); INSERT INTO CUSTOMER_STATION VALUES ( '00006', '0000000006', '0000006', '19-Aug-2015' ); INSERT INTO CUSTOMER_STATION VALUES ( '00007', '0000000007', '0000007', '30-May-2015' ); INSERT INTO CUSTOMER_STATION VALUES ( '00008', '0000000008', '0000008', '23-Feb-2015' ); INSERT INTO CUSTOMER_STATION VALUES ( '00009', '0000000009', '0000009', '13-Aug-2015' ); INSERT INTO CUSTOMER_STATION VALUES ( '00010', '0000000010', '0000010', '18-Mar-2015' ); NON_SUBSCRIBER TABLE INSERT INTO NON_SUBSCRIBER VALUES ( '0000000003',

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'30Day', '14-Jan-2015', '14-Feb-2015' ); INSERT INTO NON_SUBSCRIBER VALUES ( '0000000005', '30Day', '20-Jan-2015', '20-Feb-2015' ); INSERT INTO NON_SUBSCRIBER VALUES ( '0000000007', '30Day', '07-Aug-2015', '07-Sep-2015' ); INSERT INTO NON_SUBSCRIBER VALUES ( '0000000009', '30Day', '17-Mar-2015', '17-Apr-2015' ); INSERT INTO NON_SUBSCRIBER VALUES ( '0000000013', '30Day', '07-Nov-2015', '07-Dec-2015' ); INSERT INTO NON_SUBSCRIBER VALUES ( '0000000011', '30Day', '07-Dec-2015', '07-Jan-2015' ); INSERT INTO NON_SUBSCRIBER VALUES ( '0000000015', '30Day', '07-Oct-2015', '07-Nov-2015' ); INSERT INTO NON_SUBSCRIBER VALUES ( '0000000017', '30Day', '08-Oct-2015', '08-Nov-2015'

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); INSERT INTO NON_SUBSCRIBER VALUES ( '0000000019', '30Day', '15-Oct-2015', '15-Nov-2015' ); RECORDLABEL TABLE INSERT INTO RECORDLABEL VALUES ('001','001','Roxxy',.07); INSERT INTO RECORDLABEL VALUES ('002','002','City',.04); INSERT INTO RECORDLABEL VALUES ('003','003','Dixie',.05); INSERT INTO RECORDLABEL VALUES ('004','004','Shelton',.06); INSERT INTO RECORDLABEL VALUES ('005','005','Dancxing',.07); INSERT INTO RECORDLABEL VALUES ('006','006','Beijing',.08); INSERT INTO RECORDLABEL VALUES ('007','007','Shanghai',.09); INSERT INTO RECORDLABEL VALUES ('008','008','Barca',.01); INSERT INTO RECORDLABEL VALUES ('009','009','Madrid',.03); INSERT INTO RECORDLABEL VALUES ('010','010','LA',.04); SONG TABLE INSERT INTO SONG VALUES ('0000001','0000000001','001','Flying','Rock','Plus Boys','14-Oct-1961'); INSERT INTO SONG VALUES ('0000002','0000000002','002','Camping','Latin','Jersey Boys','10-Feb-1962'); INSERT INTO SONG VALUES ('0000003','0000000003','003','Hiking','Rock','Princeroyce','18-Jan-1963'); INSERT INTO SONG VALUES ('0000004','0000000004','004','Sleeping','Rock','Nickyjam','05-Mar-1964'); INSERT INTO SONG VALUES ('0000005','0000000005','005','Crying','Rock','EnriqueInglesias','12-Apr-1965'); INSERT INTO SONG VALUES ('0000006','0000000006','006','Jumping','Rock','Shakira','22-May-1966'); INSERT INTO SONG VALUES ('0000007','0000000007','007','Falling','Rock','JustinBieber','25-Jun-1967'); INSERT INTO SONG VALUES ('0000008','0000000008','008','Laughing','Rock','SelenaGomez','30-Jul-1968'); INSERT INTO SONG VALUES ('0000009','0000000009','009','Coding','Rock','LittleJ','11-Aug-1969'); INSERT INTO SONG VALUES ('0000010','0000000010','010','Sitting','Rock','Mr.P','09-Sep-2015');

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STATION TABLE INSERT INTO STATION VALUES ('00001','00001'); INSERT INTO STATION VALUES ('00002','00002'); INSERT INTO STATION VALUES ('00003','00003'); INSERT INTO STATION VALUES ('00004','00004'); INSERT INTO STATION VALUES ('00005','00005'); INSERT INTO STATION VALUES ('00006','00006'); INSERT INTO STATION VALUES ('00007','00007'); INSERT INTO STATION VALUES ('00008','00008'); INSERT INTO STATION VALUES ('00009','00009'); INSERT INTO STATION VALUES ('00010','00010'); STATION_SONG TABLE INSERT INTO STATION_SONG VALUES ('0000000001','00001','0000001' ); INSERT INTO STATION_SONG VALUES ('0000000002','00002','0000002' ); INSERT INTO STATION_SONG VALUES ('0000000003','00003','0000003' ); INSERT INTO STATION_SONG VALUES ('0000000004','00004','0000004' ); INSERT INTO STATION_SONG VALUES ('0000000005','00005','0000005' ); INSERT INTO STATION_SONG VALUES ('0000000006','00006','0000006' ); INSERT INTO STATION_SONG VALUES ('0000000007','00007','0000007' ); INSERT INTO STATION_SONG VALUES ('0000000008','00008','0000008' ); INSERT INTO STATION_SONG VALUES ('0000000009','00009','0000009' ); INSERT INTO STATION_SONG VALUES ('0000000010','00010','0000010' ); SUBSCRIBER TABLE INSERT INTO SUBSCRIBER VALUES ( '0000000002', '000001', 1234123412341234,

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12,2016,123, 'N', '1MONTH', '24-Dec-2015' ); INSERT INTO SUBSCRIBER VALUES ( '0000000004', '000002', 8843147296055194, 09,2017,492, 'N', '1MONTH', '18-Dec-2015' ); INSERT INTO SUBSCRIBER VALUES ( '0000000006', '000003', 0752117991236829, 09,2017,422, 'N', '1MONTH', '03-Jan-2015' ); INSERT INTO SUBSCRIBER VALUES ( '0000000008', '000004', 0752132991236829, 03,2015,422, 'N', 'TRIAL', '20-Dec-2015' ); INSERT INTO SUBSCRIBER VALUES ( '0000000010', '000005', 0752117211236829, 09,2015,422, 'N', '1MONTH', '03-Dec-2015' ); INSERT INTO SUBSCRIBER VALUES ( '0000000012', '000006', 0752117992336829, 05,2017,422, 'N',

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'1MONTH', '07-Dec-2015' ); INSERT INTO SUBSCRIBER VALUES ( '0000000014', '000007', 0752123991236829, 09,2015,414, 'N', '1MONTH', '15-Dec-2015' ); INSERT INTO SUBSCRIBER VALUES ( '0000000016', '000008', 0752117991236829, 09,2017,422, 'N', 'Bi-yearly', '03-Jan-2015' ); INSERT INTO SUBSCRIBER VALUES ( '0000000018', '000009', 1234567899876543, 09,2017,422, 'N', '3Year', '20-Nov-2018' ); INSERT INTO SUBSCRIBER VALUES ( '0000000020', '000010', 1234567899876543, 09,2017,422, 'N', '1Year', '20-Dec-2016' ); SUBSCRIPTION TABLE INSERT INTO SUBSCRIPTION VALUES (‘000001’,'M'); INSERT INTO SUBSCRIPTION VALUES (‘000002’,'M'); INSERT INTO SUBSCRIPTION VALUES (‘000003’,'M'); INSERT INTO SUBSCRIPTION VALUES (‘000004’,'M'); INSERT INTO SUBSCRIPTION VALUES ('000005','M'); INSERT INTO SUBSCRIPTION VALUES ('000006','M'); INSERT INTO SUBSCRIPTION VALUES ('000007','M');

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INSERT INTO SUBSCRIPTION VALUES ('000008','Bi'); INSERT INTO SUBSCRIPTION VALUES ('000009','3Y'); INSERT INTO SUBSCRIPTION VALUES ('000010','Y');

Implemented Database Structure This is the implementation model after it has already been created in the database management system. This is different from the ER Diagram as can be referenced above because it only contains the many to many relationships with the relations having their own attributes on the parent side.

Properties of Fields of Tables in Implemented Database We needed to decipher what type of data would go in to each column of the table, be it numerical, relating to time or data, alphanumerical, or other types of data cases. Table: Account Executive EID = The identification number assigned to each executive. ENAME = The name of the executive. Table: Album ALBID= The identification number assigned to each album. ARTID= The identification number assigned to each artist. ALBCOST= The price of the album. ALBNAME= The name of the album. GENRA= The genre that the album music lies within. Table: Customer_Album CUST_ALB= The identification number assigned to each customer album interaction. CID= The identification number assigned to each customer. ALBID= The identification number assigned to each album. PURCHASEALBUMTIME= The time and date when the customer purchases an album. Table: Artist ARTID= The identification number assigned to each artist. ARTNAME= The name of the artist. Table: Contact CID= The identification number assigned to each customer. CONID= The identification number of each contact that was made. CTYPE= The method by which the contact was made. NOTIFICATION= The type of notification that was provided to the customer when contacted. Table: Customer CID= The identification number assigned to each customer. CTYPE= Whether or not the customer is a subscriber. CSTREET= The street that the customer lives on. CSTATE= The state that the customer lives in. CZIP= The zipcode of the customer’s address. CCITY= The city that the customer lives in. CSIGNUP= When the customer signed up for their membership. CDOB= The date of birth of the customer. CEMAIL= The email address of the customer. CNAME= The name of the customer.

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Table: Customer_Song CUSTSONG_ID= The identification number assigned to each customer song interaction. CID= The identification number assigned to each customer. SONGID= The identification number of each song. SONGRATING= The rating that the customers gave to the song. SONGRATINGTIME= The time that the customer rated the song. SONGTYPE= The type of song that the song is categorized as. SONGSKIPTIMES= The amount of times that the song was skipped. SONGUSAGEFREQUENCY= The frequency that the song was played. LISTENINGTIME= The time that the customer listened to the song. SKIPTIMEDATE= The time that the customer skipped the song. Table: Customer_SongP CSP_ID= The id number assigned to each song that is purchased by a customer. CID= The identification number assigned to each customer. SONGID= The identification number of each song. SONG_PRICE= The price of the individual song. PURCHASETIME= The time that each song is purchased. Table: Customer_Station CUSTSTAT_ID= The id number assigned to each station listened to by a customer. CID= The identification number assigned to each customer. ALBID= The identification number assigned to each album. STATIONCREATIONTIME= The time that the station was created. Table: Non_Subscriber CID= The identification number assigned to each customer. NSDURATION= The length of time that the trial lasts. NSTARTDATE= The date that the trial was started. NSENDATE= The date that the trial ends. Table: Record Label RID= The identification number assigned to the record label. EID= The identification number assigned to the executive. RECNAME= The name of the record. PROFITRATIO= The profit ratio awarded to the record label. Table: Song SONGID= The identification number of each song. ARTID= The identification number assigned to each artist. RID= The identification number assigned to the record label.

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SNAME= The name of the song. SGENRA= The genre that the song is a part of. SARTIST= The name of the artist that created the song. SRELEASEDATE= The date that the song was released. Table: Station STATIONID= The identification number assigned to each station. STARTTYPE= The number of stars given to each station. Table: Station_Song STATSONGID= The identification number assigned to each song and station combination. STATIONID= The identification number assigned to each station. SONGID= The identification number assigned to each song. Table: Subscriber CID= The identification number assigned to each customer. SUBSELECTID= The identification number associated with subscription type. CCNUMBER= The credit card number of the customer. CCEXPMONTH= The expiration month of the subscriber’s card. CCEXPYEAR= The year that the subscriber’s card expires. CCSECURITYCODE= The security code of the customer’s card. CCPAYPALOPTION= Whether or not the customer is using PayPal. SUBSCRIPTIONTYPE= The type of subscriber that the subscriber is whether monthly yearly or bi-yearly. SDURATION= The length of the subscription. SENDDATE= The date that the payment information was processed. Table: Subscription SUBSELECTID= The identification number associated with subscription type. SUBSCRIPTIONTYPE= The type of subscriber that the subscriber is whether monthly yearly or bi-yearly.

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Queries In order to extract the data that was requested by MusicMash, the following statements were crafted and subsequently ran. These statements are vital for contributing to a MusicMash employee’s daily needs. 1. Most popular songs in a given month/year SELECT Song.SongID, Song.Sname, Customer_Song.SONGUSAGEFRequency FROM Song, Customer_Song WHERE Song.SongID=Customer_Song.SongID AND Song.SongID IN (SELECT SongID FROM (SELECT SONGID , SONGUSAGEFRequency , rank() over (order by SONGUSAGEFRequency DESC) AS rnk FROM Customer_SONG ) WHERE rnk <= 10 ); AND extract(MONTH FROM ListeningTime) = &ListeningMonth AND extract(YEAR FROM ListeningTime) = &ListeningYear; 2. Most popular artists in a given month/year SELECT Artist.ArtID,Artist.Artname, Customer_Song.SONGUSAGEFRequency FROM Song, Customer_Song, Artist WHERE Song.SongID=Customer_Song.SongID AND Song.ArtID = Artist.ArtID AND Song.SongID IN (SELECT SongID FROM (SELECT SONGID , SONGUSAGEFRequency , rank() over (order by SONGUSAGEFRequency DESC) AS rnk FROM Customer_SONG ) WHERE rnk <= 10

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) AND extract(MONTH FROM ListeningTime) = &ListeningMonth AND extract(YEAR FROM ListeningTime) = &ListeningYear; 3. Songs that are skipped most often by customers SELECT SongID, SongSkiptimes FROM (SELECT SONGID , songskiptimes , rank() over (order by Songskiptimes DESC) AS rnk FROM Customer_SONG ) WHERE rnk <= &Howmanysongs; 4. Number of days until a trial expires for each trial customer SELECT CID, SDuration, Round(senddate-sysdate) as Numberofdaystillexpiration FROM dual, subscriber WHERE SDuration = 'TRIAL' AND Round(senddate-sysdate) >= 0; 5. An ordered list of the number of days until a subscription expires for paying customers except monthly customers SELECT CID, SDuration, Round(senddate-sysdate) as Numberofdaystillexpiration FROM dual, subscriber WHERE SDuration <> 'TRIAL' AND SDuration <> '1MONTH' AND Round(senddate-sysdate) >= 0 ORDER BY Numberofdaystillexpiration DESC; 6. Most popular categories of music by gender of the customer SELECT Customer.Cgender, Customer_Song.songtype, count(Customer_Song.songtype) as Most_Popular FROM Customer, Customer_Song WHERE Customer.CID = Customer_Song.CID AND Cgender = &Gender GROUP BY Customer.Cgender, Customer_Song.songtype ORDER BY count(Customer_Song.songtype) DESC; 7. Most popular song by region of the country

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SELECT SongID, Customer_Song.Region, Max(Songusagefrequency) as Most_Popular_Song FROM Customer_Song WHERE Region = &Region GROUP BY Region,Songid ORDER BY Most_Popular_Song DESC FETCH NEXT 1 ROWS ONLY; 8. Monthly payments to record labels for purchased songs/albums. SELECT cust_alb, Customer_SongP.SongID, Recordlabel.RID, RecordLabel.Recname, Profitratio, cust_alb, Sum(Song_Price) As Revenue, (Sum(Song_Price) *Profitratio) As Monthly_Song_Payment, (Sum(Albcost)*.02) As Monthly_Album_Payment FROM Song, Customer_SongP, Recordlabel, Artist, Album, Customer_Album WHERE Customer_SongP.SongID = Song.SongID AND Song.RID = Recordlabel.RID AND Song.ArtID = Artist.ArtID AND Album.ArtID = Artist.ArtID AND Album.Albid = Customer_Album.Albid AND extract(MONTH FROM PurchaseTime) = &PurchaseSongMonth AND extract(MONTH FROM PurchaseTime) = &PurchaseAlbumMonth GROUP BY Customer_SongP.SongID, Recordlabel.RID, Profitratio, RecordLabel.Recname, albcost, cust_alb; 9. Monthly payment to account executives each month. SELECT Customer_SongP.SongID, Recordlabel.RID, AccountExec.EID, Profitratio, Sum(Song_Price) As Revenue, (Sum(Song_Price) *.02) As Monthly_Payment_to_AccountEXEC FROM Song, Customer_SongP, Recordlabel, AccountExec WHERE Customer_SongP.SongID = Song.SongID AND Song.RID = Recordlabel.RID AND Recordlabel.EID = AccountExec.EID AND extract(MONTH FROM PurchaseTime) = &PurchaseMonth /* isolates calculations for the month entered and user intuitively knows month because they entered it*/ GROUP BY Customer_SongP.SongID, Recordlabel.RID, AccountExec.EID, Profitratio; 10. Average price of music albums based on genre. SELECT Genre, AVG(Albcost) FROM ALBUM GROUP BY Genre; 11. Average number of songs each customer listens to per day.

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SELECT CID, AVG(AVGPERDAY) /*Aggregates all the average songusagefrequencies per day and divides them by the total number of days */ From Customer_SONG WHERE CID IN ( SELECT CID FROM Customer_Song WHERE ListeningTime >= ListeningTime - .5 AND ListeningTime <= ListeningTime + .5 Return AVG (Songusagefrequency) as AVGPERDAY /*returning the inner query for the average for each day, now we will add those avgperday together and divide them by total to get total avg per day */ );

User Documentation of Database User documentation for the MusicMash database will be crafted by a dedicated team of experts on the dataset. The documentation will instruct MusicMash employees on how to use the service in the most efficient and effective way possible. Advise the team of experts to include the following in the user documentation for the database: (1) Managing Database Users, (2) Modifying a Database User’s Permissions with the Control Panel, (3) Changing a Database User’s Password, (4) Connecting to a Database, (5) Accessing a Database from the Web, (6) Accessing a Database Remotely, (7) Import and Export Database Records, (8) Running Queries. Running queries will constitute a large part of what MusicMash employees will be doing day in, day out. We’ve included some documentation on what we believe will be the most frequent use-case scenarios for queries. 1. Most popular songs in a given month/year Run this query with the respective SQL code, listed above. The query will prompt you to (1) Enter Value for ListeningMonth, which refers to the month when the song was listened to by the user, and (2) Enter Value for ListeningYear, which refers to the year when the song was listened to by the user. This will return you the most popular songs in the time frame you specified. 2. Most popular artists in a given month/year Run this query with the respective SQL code, listed above. The query will prompt you to (1) Enter Value for ListeningMonth, which refers to the month when the artist was listened to by the user, and (2) Enter Value for ListeningYear, which refers to the year when the artist was listened to by the user. This will return you the most popular artists in the time frame you specified. 3. Songs that are skipped most often by customers Run this query with the respective SQL code, listed above. Running the aforementioned query will prompt you to (1) Enter value for Howmanysong. Entering this value will specify the quantity of top song skipped in descending order. This will allow the database user to produce specific reports (dashboards) for internal purposes. 4. Number of days until a trial expires for each trial customer

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Run this query with the respective SQL code, listed above. Running the aforementioned query will return the number of days until the trail expiries for each trial customer. By include our WHERE statement, we have prevented issues that may result from legacy data interfering with the current data in the query. This also allows you to keep the legacy data in the database without taking away from the queries you need to run for your business operation. 5. An ordered list of the number of days until a subscription expires for paying customers except monthly customers Run this query with the respective SQL code, listed above. Running the aforementioned query will return an ordered list of the number of the days until a subscription expires for paying customers except monthly customers. By include our WHERE statement, we have prevented issues that may result from legacy data interfering with the current data in the query. This also allows you to keep the legacy data in the database without taking away from the queries you need to run for your business operation. 6. Most popular categories of music by gender of the customer Run this query with the respective SQL code, listed above. The query will prompt you to (1) Enter Value for Gender, where Gender is defined as M, male, or F, female. Be sure to when inputting male or female in quotes: ‘M’ or ‘F’. A common mistake is using double quotes (i.e. “M” or “F”) when inputting the value. Running the aforementioned query will return the categories of music by gender. 7. Most popular song by region of the country Run this query with the respective SQL code, listed above. The query will prompt you to (1) Enter Value for Region, where Region is defined as W, West, N, North, E, East, S, South, NE, Northeast, NW, Northwest, SE, Southeast, and SW, Southwest. The aforementioned query will return the most popular song in your specified region of the country. 8. Monthly payments to record labels for purchased songs/albums. Run this query with the respective SQL code, listed above. The query will prompt you to (1) Enter value for PurchaseSongMonth, where PurchaseSongMonth is the month in which the customer purchased the song and (2) Enter value for PurchaseAlbumMonth, where PurchaseAlbmMonth is the month in which the cusomter purchased the album. The values that you are entering isolate your calculation for that specific month, allowing you to find the monthly payment for songs or albums for that specific month.

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Running the aforementioned query will return the monthly payments for purchased songs and albums. 9. Monthly payment to account executives each month. Run this query with the respective SQL code, listed above. The query will prompt you to (1) Enter value for PurchaseMonth, where PurchaseMonth is the month in which the songs were purchased that the account executive will get paid for. Running the aforementioned query will return monthly payment to account executives each month. 10. Average price of music albums based on genre. Run this query with the respective SQL code, listed above. Running the aforementioned query will return average price of music albums based on genre 11. Average number of songs each customer listens to per day. Run this query with the respective SQL code, listed above. Running the aforementioned query will return the average number of songs each customer listens to in the past (+/-) 12 hours. Training and Use of Database The SWOT team researched best practices at companies similar to MusicMash to develop recommendations The biggest database variable are the people using them. To overcome this, training is required to use the database correctly and ensure people within the company are best equip to use the database to it’s fullest potential. The last thing your organization wants is for a new employee to break the database. To have new hires hit the ground running, train them on the database by way of (1) a seminar, (2) handouts, (3) restrict access, (4) provide opportunities for further training. A proven way to train employees is to have them learn by doing. Hold training on-site seminars—brining employees on in rotations if necessary—and explain all aspects of the database. Emphasize the importance of quality assurance to employees. Ensure the seminar concise and interactive, as the content and be try at time and we want to keep employees engaged throughout the seminar’s duration. During your seminar, it may be useful to provide handouts to your employees with key facts on the use of the database. Handouts will ensure that

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employees will take notes on what you are saying, and give them something to reference when they use the database following the training session. Make the handout simple, clean, and concise. Restrict employee access to only the parts of the database each individual employee needs to access. We don’t want to grant root access to all users. Provide further opportunities for employees to expand their skill set with respect to the database. Hold optional advanced seminars every 3 months to allow for employees to grow. Grant employees access to existing Webinars and courses (i.e. Lynda.com) so they can grow their knowledge as it suits them, at their on pace, on their own time. Technology Issues A major technology issue we encountered at the start of Phase 3, was remembering to save as we continued to work. We inserted all of our CREATE TABLE statements and did not click the “Commit Changes” button when quitting the SQL program. Therefore, when we logged back on to the database we were surprised to see that all of our tables were missing. This was a minor setback when working on our project, as we had to insert these statements into the system once again. One of the limitations we found when working with SQL was the ability to only run the program when connected to UA Wi-Fi. This made it difficult as all team members had to allocate time to meet up on campus to work on this project, despite everyone’s busy scheduling. If SQL program could function on other Wi-Fi networks, we would have more time to work on the project and not be restricted to just working on it at school. An addition problem that we ran into with SQL was the inability for multiple users to be signed into the database. When this occurred the database would either be extremely slow or constantly log out leaving the database useless for both users. This would also happen if one user was using a VPN and another user was on UAWIFI. The challenge with the aforementioned scenario is that group members did not know when another member was logged in. The last technology issue was the fact that some of our group members used Mac and other’s used PC. SQL looks a little different on the two platforms therefore it was difficult for group members to collaborate on each other’s platform. Formatting was a huge issue combined with the google docs issue and Mac’s inability to decipher proper apostrophes.

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Lessons Learned One of the most important lessons we learned over the course for the semester while working on this project is the importance of attention to detail. While imputing our SQL codes into the database, we encounter many errors. A handful of these errors were caused simply because we did not pay close enough attention when entering the sequences into the database. Forgetting to add the semicolon after each statement and missing punctuations were common mistakes we made at in the beginning. This was because we were quickly entering the create table and insert statements while utilizing the Google Docs application, where we had originally typed statements. When copying and pasting these statements over, the formatting of them changed as the functions in Mac OS X copy/paste function altered some of the formatting. While we were trying to be time efficient in copying and pasting multiple statements at a time, we actually spent more time trying to search for where the error occurred in each line and correct the statement. Moving forward, we learned to carefully type these statements directly into the program to ensure we had the correct elements and formatting for each. Once we nailed this down, we were able to efficiently enter the data. The database itself was instrumental for learning lessons for the project. The first lesson that SQL taught us was regarding foreign keys. A foreign key must be added from an existing primary key in SQL. When we tried to correct this issue by adding a second primary key, SQL will not allow it. After dropping multiple tables and reinserting data we realized that the reason this foreign kay could not be added was data redundancy. The data was redundant and should have only been placed in one of our two tables. This second example of how SQL taught us a lesson was in inserting the data. When we tried to insert data we had to have more than 10 entries in the customer table. This is because customers were later sub grouped into subscribers and non subscribers. If we did not add more than 10 entries in our customer table, then the subscriber and non subscriber tables would not have enough data per the instructions of the assignment. This was easily rectified by the addition of 10 subscribers and 10 non subscribers in our customer table.