├── DBMS Retail Application ├── CSV Files │ ├── Voucher.csv │ ├── Product group.csv │ ├── Supplier.csv │ ├── Reviews.csv │ ├── Zipcode.csv │ ├── Product Details.csv │ ├── Product.csv │ ├── Employee.csv │ ├── address.csv │ ├── Bill.csv │ ├── Order Product.csv │ ├── Customer.csv │ ├── Customer Fix.csv │ ├── Orders.csv │ ├── order.csv │ ├── Employee New.csv │ └── Payment.csv ├── EER3MFA.jpg ├── Result report.docx ├── DBMS Retail Application DatabaseMFA.pdf ├── README.md ├── SQLQueries,Triggers,StoredProcedures,Views.sql └── SQL │ └── Generated.SQL ├── README.md └── Trial.R /DBMS Retail Application/CSV Files/Voucher.csv: -------------------------------------------------------------------------------- 1 | Voucher_ID,Discount% 2 | V1,10 3 | V2,20 4 | V3,30 5 | V4,40 6 | V5,50 7 | -------------------------------------------------------------------------------- /DBMS Retail Application/CSV Files/Product group.csv: -------------------------------------------------------------------------------- 1 | Group_ID,Group_Name 2 | 100,Electronics 3 | 200,Clothing 4 | 300,Shoes 5 | -------------------------------------------------------------------------------- /DBMS Retail Application/EER3MFA.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Uppalapa/Database-Projects/HEAD/DBMS Retail Application/EER3MFA.jpg -------------------------------------------------------------------------------- /DBMS Retail Application/Result report.docx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Uppalapa/Database-Projects/HEAD/DBMS Retail Application/Result report.docx -------------------------------------------------------------------------------- /DBMS Retail Application/DBMS Retail Application DatabaseMFA.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Uppalapa/Database-Projects/HEAD/DBMS Retail Application/DBMS Retail Application DatabaseMFA.pdf -------------------------------------------------------------------------------- /DBMS Retail Application/CSV Files/Supplier.csv: -------------------------------------------------------------------------------- 1 | Supplier_ID,Supplier_Name,Supply_Quantity 2 | S001,Zara,200 3 | S002,Gucci,300 4 | S003,Lacoste,250 5 | S004,Nike,200 6 | S005,Addidas,300 7 | S006,Star,250 8 | S007,Apple,150 9 | S008,Lenevo,200 10 | S009,Hp,100 11 | -------------------------------------------------------------------------------- /DBMS Retail Application/CSV Files/Reviews.csv: -------------------------------------------------------------------------------- 1 | Quality_Rating,Defect%,Review_ID,Product_ID 2 | 7,10,RE01,PR101 3 | 7,10,RE02,PR102 4 | 7,10,RE03,PR103 5 | 7,10,RE04,PR104 6 | 7,10,RE05,PR105 7 | 7,10,RE06,PR106 8 | 7,10,RE07,PR107 9 | 9,0,RE08,PR108 10 | 9,0,RE09,PR109 11 | 9,0,RE10,PR110 12 | 9,0,RE11,PR111 13 | 9,0,RE12,PR112 14 | 9,0,RE13,PR113 15 | 9,0,RE14,PR114 16 | 9,0,RE15,PR115 17 | 9,0,RE16,PR116 18 | 9,0,RE17,PR117 19 | 7,10,RE18,PR118 20 | 7,10,RE19,PR119 21 | 7,10,RE20,PR120 22 | 7,10,RE21,PR121 23 | 7,10,RE22,PR122 24 | 7,10,RE23,PR123 25 | 7,10,RE24,PR124 26 | 7,10,RE25,PR125 27 | 7,10,RE26,PR126 28 | 7,10,RE27,PR127 29 | 7,10,RE28,PR128 30 | 8,5,RE29,PR129 31 | 8,5,RE30,PR130 32 | 8,5,RE31,PR131 33 | 8,5,RE32,PR132 34 | 8,4,RE33,PR133 35 | 8,4,RE34,PR134 36 | 9,0,RE35,PR135 37 | 9,0,RE36,PR136 38 | 5,20,RE37,PR137 39 | 4,30,RE38,PR138 40 | 9,0,RE39,PR139 41 | 9,0,RE40,PR140 42 | -------------------------------------------------------------------------------- /DBMS Retail Application/CSV Files/Zipcode.csv: -------------------------------------------------------------------------------- 1 | State,Zipcode_ID,City 2 | Florida,11000,Miami 3 | Florida,11001,Orlando 4 | Florida,11002,Tampa 5 | Florida,11003,Fort 6 | Florida,11004,Jacksonville 7 | Florida,11005,Key West 8 | Florida,11006,West Palm 9 | Florida,11007,Naples 10 | Florida,11008,St.Peterbrough 11 | Florida,11009,Daytona 12 | Alaska,22000,Anchorage 13 | Alaska,22001,Juneau 14 | Alaska,22002,Fair Banks 15 | Alaska,22003,Ketchikan 16 | Alaska,22004,Wasilla 17 | Alaska,22005,Sitka 18 | Alaska,22006,Kodiak 19 | Massachusetts,33000,Boston 20 | Massachusetts,33001,Framingham 21 | Massachusetts,33002,Somerville 22 | Massachusetts,33003,Playmouth 23 | Massachusetts,33004,Lowll 24 | Massachusetts,33005,Newton 25 | Massachusetts,33006,Quincy 26 | California,44000,Los Angeles 27 | California,44001,Sanfrancisco 28 | California,44002,Sandiego 29 | California,44003,San Jose 30 | Kansas,55000,Kansas City 31 | Kansas,55001,Topeka 32 | Kansas,55002,Wichida 33 | Kansas,55003,Over land 34 | -------------------------------------------------------------------------------- /DBMS Retail Application/CSV Files/Product Details.csv: -------------------------------------------------------------------------------- 1 | Product_ID,Weight,Width,Height,Colour 2 | PR101,8,15,13,White 3 | PR102,8,15,13,White 4 | PR103,8,15,12,Silver 5 | PR104,6,15,12,Silver 6 | PR105,6,13,12,Black 7 | PR106,6,13,12,Black 8 | PR107,6,13,12,Black 9 | PR108,4,11,12,Silver 10 | PR109,4,11,12,Silver 11 | PR110,4,11,12,Silver 12 | PR111,4,10,10,Silver 13 | PR112,3,1.8,6.8,Silver 14 | PR113,3,1.8,6.8,Black 15 | PR114,3,1.8,6.8,Black 16 | PR115,3,1.8,6.8,Black 17 | PR116,3,1.8,6.8,Black 18 | PR117,3,1.8,6.8,Black 19 | PR118,1,1.8,7.2,Rose Gold 20 | PR119,1,1.8,7.2,Rose Gold 21 | PR120,1,1.8,8,Rose Gold 22 | PR121,2,1.8,8.73,Black 23 | PR122,2,1.8,6.27,Black 24 | PR123,2,1.8,6.27,Black 25 | PR124,2,1.8,6.27,Black 26 | PR125,2,1.8,6.27,Black 27 | PR126,2,1.8,6.27,Black 28 | PR127,2,1.8,6.27,Black 29 | PR128,2,1.8,6.27,Black 30 | PR129,1,1.8,6.27,Black 31 | PR130,1,1.8,6.27,Black 32 | PR131,1,1.8,6.27,Black 33 | PR132,1,1.8,6.27,White 34 | PR133,1,1.8,6.27,Grey 35 | PR134,1,1.8,6.27,Grey 36 | PR135,1,1,10,Brown 37 | PR136,1,1,9,Black 38 | PR137,2,1,8,White 39 | PR138,2,1,7,Brown 40 | PR139,1,1,6,Black 41 | PR140,1,1,6,Brown 42 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Database Management for Retail Application 2 | * Designed a relational database schema using TOAD data modeler. 3 | * Created multiple tables and managed the retail stores’ data in MySQL. 4 | * Applied database objects like triggers, stored procedures, views, functions on the database. 5 | * Generated reports which helped the retail organization to evaluate their sales, analyze sales for this season and forecast sales for next season. 6 | * Used R for visuialization 7 | 8 | ### ER Diagram for Retail Application 9 | #### ER Diagram for Retail Application after Normalization 10 | ![333](https://user-images.githubusercontent.com/25045759/27304878-8679f712-550d-11e7-8dd3-d2ad92ee5289.jpg) 11 | 12 | ### Data Vizualization using R 13 | ![rplot](https://user-images.githubusercontent.com/25045759/28239207-7943bfa2-6934-11e7-8592-5f0448e8c19a.png) 14 | ![rplot01](https://user-images.githubusercontent.com/25045759/28239206-7943588c-6934-11e7-9254-9fe9a613b11f.png) 15 | 16 | 17 | ### Project README: README 18 | ### Project Link: PROJECT CODE 19 | ### Result Report: REPORT 20 | -------------------------------------------------------------------------------- /DBMS Retail Application/CSV Files/Product.csv: -------------------------------------------------------------------------------- 1 | Product_ID,Product_Name,Available_Number,Group_ID,Supplier_ID 2 | PR101,Lenevo Flex,25,100,S008 3 | PR102,Lenevo Yoga,25,100,S008 4 | PR103,Lenevo Think Pad,25,100,S008 5 | PR104,Mac Book Pro,27,100,S007 6 | PR105,Mac Mini,29,100,S007 7 | PR106,Mac Air,31,100,S007 8 | PR107,Mac Book,33,100,S007 9 | PR108,Mac Desktops,35,100,S007 10 | PR109,Hewlett Mini,37,100,S006 11 | PR110,Hewlett Desktop,39,100,S006 12 | PR111,Lenevo 5Note,40,100,S008 13 | PR112,Lenevo Phab,40,100,S008 14 | PR113,Lenevo A8,40,100,S008 15 | PR114,Lenevo K10,40,100,S008 16 | PR115,IphoneS7 Plus,40,100,S007 17 | PR116,IphoneS6 Plus,40,100,S007 18 | PR117,IphoneS4,21,100,S007 19 | PR118,IphoneS5,22,100,S007 20 | PR119,IphoneS6,23,100,S007 21 | PR120,IphoneS7,24,100,S007 22 | PR121,Zara Women Frocks,25,200,S002 23 | PR122,Zara Sweat Shirts,26,200,S002 24 | PR123,Zara Trousers,27,200,S002 25 | PR124,Zara Tshirt,28,200,S002 26 | PR125,Zara Hood Shirt,29,200,S002 27 | PR126,Gucci Sweat Shirt,30,200,S003 28 | PR127,Gucci Shirts,31,200,S003 29 | PR128,Gucci Women Frocks,32,200,S003 30 | PR129,Gucci Women Shirts,33,200,S003 31 | PR130,Gucci Men Tshirts,34,200,S003 32 | PR131,Gucci Women Tshirts,35,200,S003 33 | PR132,Lacoste Women Tshirts,22,200,S001 34 | PR133,Lacoste Mens Tshirts,22,200,S001 35 | PR134,Lacoste Shorts,22,200,S001 36 | PR135,Lacoste Shirts,17,200,S001 37 | PR136,Addidas Formal Shoes,18,300,S005 38 | PR137,Addidas sneakers,19,300,S005 39 | PR138,Nike Formal Shoes,20,300,S003 40 | PR139,Nike Sports Shoes,21,300,S003 41 | PR140,Star Sneakers,12,300,S001 42 | -------------------------------------------------------------------------------- /Trial.R: -------------------------------------------------------------------------------- 1 | #Reading th csv File 2 | customer=read.csv("Customer Fix.csv") 3 | 4 | str(customer) 5 | summary(customer) 6 | 7 | ######remove coloumns 8 | customer = customer[-c( 2,3)] 9 | summary(customer) 10 | #########Plots######### 11 | #plot( table(customer$Customer_ID) , table(customer$Customer_Type) , xlab = "Customer" , ylab = "Customer type") 12 | 13 | ##Histogram 14 | #hist(customer$Customer_Type , xlab = "Customer_Type" ,ylab = "Frequency" , main = "Histogram of type of customer" ) 15 | barplot(table(customer$Customer_Type)) 16 | 17 | #install.packages("DMwR") 18 | library(DMwR) 19 | #install.packages("caret") 20 | library(caret) 21 | #install.packages("dplyr") 22 | library(dplyr) 23 | ### customer$Customer_ID <- as.factor(customer$Customer_ID) 24 | 25 | customer=customer[ -c(2,3,4,5) ] 26 | str(customer) 27 | summary(customer) 28 | preproc <- preProcess(customer) 29 | custNorm <- predict(preproc, customer) 30 | summary(custNorm) 31 | custNorm=scale(customer) 32 | summary(custNorm) 33 | 34 | set.seed(5000) 35 | clustKMC <- kmeans(custNorm, centers = 3) 36 | 37 | table(custKMC$cluster) 38 | install.packages("cluster") 39 | install.packages("fpc") 40 | library(fpc) 41 | library(cluster) 42 | plotcluster(custNorm, clustKMC$cluster) 43 | clusplot(custNorm, clustKMC$cluster, color=TRUE, shade=TRUE, 44 | labels=2, lines=0) 45 | normcluster1 <- subset(custNorm, custKMC$cluster == 1) 46 | summary(normcluster1) 47 | cluster1=unscale(normcluster1,custNorm) 48 | summary(cluster1) 49 | 50 | normcluster2 <- subset(custNorm, custKMC$cluster == 2) 51 | summary(normcluster2) 52 | cluster2=unscale(normcluster2,custNorm) 53 | summary(cluster2) 54 | 55 | normcluster3 <- subset(custNorm, custKMC$cluster == 3) 56 | summary(normcluster3) 57 | cluster3=unscale(normcluster3,custNorm) 58 | summary(cluster3) 59 | 60 | -------------------------------------------------------------------------------- /DBMS Retail Application/CSV Files/Employee.csv: -------------------------------------------------------------------------------- 1 | Designation,Department,Join_Date,ssn,Salary,Employee_ID,Employee_Name,Employee_Type 2 | Marketer,Marketing,2/12/2016,501965640,3000,E100,Mia,Full Time 3 | Sales Person,Sales,5/19/2016,448454504,1000,E101,Mia,Full Time 4 | Financial Advisor,Finance,10/21/2016,178408516,4000,E102,Mia,Full Time 5 | Business Analyst,Finance,8/18/2016,697367249,4000,E103,Mia,Full Time 6 | Accountant,Finance,1/18/2016,282314775,1200,E104,Mia,Full Time 7 | PC Assistants,Billing,3/10/2016,210794068,1300,E105,Mia,Full Time 8 | PC Assistants,Billing,11/25/2016,448101338,1300,E106,Mia,Full Time 9 | PC Assistants,Billing,11/5/2016,162274487,1300,E107,Leoni,Full Time 10 | PC Assistants,Billing,11/21/2016,583021048,1300,E108,Leoni,Full Time 11 | PC Assistants,Billing,5/4/2016,373888988,1300,E109,Leoni,Full Time 12 | PC Assistants,Billing,6/26/2016,432253711,1300,E110,Leoni,Full Time 13 | PC Assistants,Billing,5/14/2016,368292987,1300,E111,Leoni,Full Time 14 | PC Assistants,Billing,2/26/2016,759909891,1300,E112,Leoni,Full Time 15 | PC Assistants,Billing,11/29/2016,355492520,1300,E113,Marty,Full Time 16 | PC Assistants,Billing,8/19/2016,420485178,1300,E114,Marty,Full Time 17 | PC Assistants,Billing,1/8/2016,388145184,1300,E115,Marty,Full Time 18 | PC Assistants,Billing,11/18/2016,273173687,1300,E116,Bob,Full Time 19 | PC Assistants,Billing,4/10/2016,435797043,1300,E117,Bob,Full Time 20 | PC Assistants,Billing,4/22/2016,205203530,1300,E118,Bob,Full Time 21 | PC Assistants,Billing,1/31/2016,758165151,1300,E119,Bob,Part Time 22 | PC Assistants,Billing,7/1/2016,318277304,1300,E120,Peter,Part Time 23 | PC Assistants,Billing,4/12/2016,916118821,1300,E121,Peter,Part Time 24 | PC Assistants,Billing,9/16/2016,507645475,1300,E122,Joanna,Part Time 25 | Sales Advisor,Sales,4/27/2016,482702342,3000,E123,Joanna,Part Time 26 | Sales Advisor,Sales,8/19/2016,916799612,3000,E124,Visha,Part Time 27 | Sales Advisor,Sales,3/7/2016,552599525,3000,E125,Visha,Part Time 28 | Sales Advisor,Sales,7/26/2016,132527849,3000,E126,Ruby,Part Time 29 | Sales Person,Sales,12/7/2016,406234803,1000,E127,Ashley,Part Time 30 | Sales Person,Sales,5/2/2016,500963559,1000,E128,Stephanie,Part Time 31 | -------------------------------------------------------------------------------- /DBMS Retail Application/CSV Files/address.csv: -------------------------------------------------------------------------------- 1 | Address_ID,Apartment_Number,Street,Apartment_Name,Customer_ID,, 2 | CA100,14,Tetlow,Emerald,10001,,1 3 | CA101,13,Palace Road,Emerald,10002,, 4 | CA102,18,New England,Emerald,10003,,3 5 | CA103,12,Brookline,Emerald,10004,, 6 | CA104,12,Heath Street,Emerald,10005,, 7 | CA105,20,Cambridge Road,Emerald,10006,, 8 | CA106,19,North West Avenue,Emerald,10007,, 9 | CA107,11,South West Ave,Westglow,10008,, 10 | CA108,17,Huntington Ave,Westglow,10009,, 11 | CA109,16,Indiana Street,Westglow,10010,,2 12 | CA110,11,Park Main,Westglow,10011,, 13 | CA111,20,Riddle Street,Westglow,10012,, 14 | CA112,13,Charles Street,Westglow,10013,, 15 | CA113,10,Hill Side,Gurnet,10014,, 16 | CA114,19,Clarks Hill,Gurnet,10015,, 17 | CA115,14,Mission Main,Gurnet,10016,, 18 | CA116,10,Hay Market,Gurnet,10017,, 19 | CA117,19,Masson Road,Gurnet,10018,, 20 | CA118,20,New Burn,Gurnet,10019,, 21 | CA119,16,Oak Ter,Gurnet,10000,, 22 | CA120,10,Oak Ter,Gurnet,20000,, 23 | CA121,19,Oak Ter,Oak Burn,20001,, 24 | CA122,11,Oak Ter,Oak Burn,20002,, 25 | CA123,19,Oak Ter,Oak Burn,20003,, 26 | CA124,11,Oak Ter,Oak Burn,20004,, 27 | CA125,17,Oak Ter,Oak Burn,20005,, 28 | CA126,13,Oak Ter,Oak Burn,20006,, 29 | CA127,14,Clarks Hill,Oak Burn,20007,, 30 | CA128,10,Clarks Hill,Mariposa,20008,, 31 | CA129,13,Clarks Hill,Mariposa,20009,, 32 | CA130,17,Clarks Hill,Mariposa,20010,, 33 | CA131,20,Clarks Hill,Mariposa,20011,, 34 | CA132,19,Clarks Hill,Mariposa,20012,, 35 | CA133,10,Clarks Hill,Mariposa,20013,, 36 | CA134,11,Clarks Hill,Mariposa,20014,, 37 | CA135,18,Clarks Hill,Mariposa,20015,, 38 | CA136,12,Clarks Hill,Mariposa,20016,, 39 | CA137,16,Charles Street,Mariposa,20017,, 40 | CA138,12,Charles Street,Mariposa,20018,, 41 | CA139,10,Charles Street,Harvester ,20019,, 42 | CA140,19,Charles Street,Harvester ,20020,, 43 | CA141,14,Charles Street,Harvester ,30000,, 44 | CA142,17,Charles Street,Harvester ,30001,, 45 | CA143,10,Charles Street,Harvester ,30002,, 46 | CA144,16,North West Avenue,Marcy,30003,, 47 | CA145,11,North West Avenue,Marcy,30004,, 48 | CA146,16,North West Avenue,Marcy,30005,, 49 | CA147,16,North West Avenue,Marcy,30006,, 50 | CA148,13,North West Avenue,Marcy,30007,, 51 | CA149,12,North West Avenue,Marcy,30008,, 52 | -------------------------------------------------------------------------------- /DBMS Retail Application/CSV Files/Bill.csv: -------------------------------------------------------------------------------- 1 | Billing_ID,Amount_Paid,Voucher_ID,Payment_ID,Order_ID 2 | B1000,2000,V5,P10,O100 3 | B1001,2000,V5,P11,O101 4 | B1002,2000,V5,P12,O102 5 | B1003,2000,V5,P13,O103 6 | B1004,1700,V5,P14,O104 7 | B1005,1700,V5,P15,O105 8 | B1006,1700,V5,P16,O106 9 | B1007,1700,V5,P17,O107 10 | B1008,1600,V5,P18,O108 11 | B1009,1600,V5,P19,O109 12 | B1010,1600,V5,P20,O110 13 | B1011,1600,V5,P21,O111 14 | B1012,1600,V5,P22,O112 15 | B1013,1600,V5,P23,O113 16 | B1014,1500,V4,P24,O114 17 | B1015,1500,V4,P25,O115 18 | B1016,1500,V4,P26,O116 19 | B1017,1500,V4,P27,O117 20 | B1018,1500,V4,P28,O118 21 | B1019,1500,V4,P29,O119 22 | B1020,1500,V4,P30,O120 23 | B1021,1200,V4,P31,O121 24 | B1022,1200,V4,P32,O122 25 | B1023,1200,V4,P33,O123 26 | B1024,1200,V4,P34,O124 27 | B1025,1200,V4,P35,O125 28 | B1026,1200,V4,P36,O126 29 | B1027,1000,V3,P37,O127 30 | B1028,1000,V3,P38,O128 31 | B1029,1000,V3,P39,O129 32 | B1030,1000,V3,P40,O130 33 | B1031,1000,V3,P41,O131 34 | B1032,1000,V3,P42,O132 35 | B1033,1000,V3,P43,O133 36 | B1034,1000,V3,P44,O134 37 | B1035,1000,V3,P45,O135 38 | B1036,1000,V3,P46,O136 39 | B1037,1000,V3,P47,O137 40 | B1038,1000,V3,P48,O138 41 | B1039,1000,V3,P49,O139 42 | B1040,1000,V3,P50,O140 43 | B1041,1000,V3,P51,O141 44 | B1042,1000,V3,P52,O142 45 | B1043,900,V3,P53,O143 46 | B1044,900,V3,P54,O144 47 | B1045,900,V3,P55,O145 48 | B1046,600,V2,P56,O146 49 | B1047,600,V2,P57,O147 50 | B1048,600,V2,P58,O148 51 | B1049,600,V2,P59,O149 52 | B1050,600,V2,P60,O150 53 | B1051,600,V2,P61,O151 54 | B1052,600,V2,P62,O152 55 | B1053,600,V2,P63,O153 56 | B1054,600,V2,P64,O154 57 | B1055,400,V2,P65,O155 58 | B1056,400,V2,P66,O156 59 | B1057,400,V2,P67,O157 60 | B1058,400,V2,P68,O158 61 | B1059,400,V2,P69,O159 62 | B1060,300,V1,P70,O160 63 | B1061,300,V1,P71,O161 64 | B1062,300,V1,P72,O162 65 | B1063,300,V1,P73,O163 66 | B1064,300,V1,P74,O164 67 | B1065,200,V1,P75,O165 68 | B1066,200,V1,P76,O166 69 | B1067,200,V1,P77,O167 70 | B1068,200,V1,P78,O168 71 | B1069,200,V1,P79,O169 72 | B1070,200,V1,P80,O170 73 | B1071,200,V1,P81,O171 74 | B1072,200,V1,P82,O172 75 | B1073,100,V1,P83,O173 76 | B1074,100,V1,P84,O174 77 | B1075,100,V1,P85,O175 78 | B1076,100,V1,P86,O176 79 | B1077,100,V1,P87,O177 80 | B1078,100,V1,P88,O178 81 | B1079,100,V1,P89,O179 82 | B1080,50,V1,P90,O180 83 | B1081,50,V1,P91,O181 84 | B1082,50,V1,P92,O182 85 | B1083,50,V1,P93,O183 86 | B1084,50,V1,P94,O184 87 | B1085,50,V1,P95,O185 88 | B1086,50,V1,P96,O186 89 | B1087,50,V1,P97,O187 90 | -------------------------------------------------------------------------------- /DBMS Retail Application/CSV Files/Order Product.csv: -------------------------------------------------------------------------------- 1 | Quantity,Product_ID,Order_ID,OrderProduct_ID 2 | 2,PR101,O100,OP01 3 | 1,PR101,O101,OP02 4 | 4,PR101,O102,OP03 5 | 1,PR104,O103,OP04 6 | 1,PR105,O104,OP05 7 | 1,PR106,O105,OP06 8 | 1,PR106,O106,OP07 9 | 4,PR106,O107,OP08 10 | 3,PR106,O108,OP09 11 | 5,PR106,O109,OP10 12 | 6,PR106,O110,OP11 13 | 3,PR112,O111,OP12 14 | 5,PR113,O112,OP13 15 | 3,PR114,O113,OP14 16 | 2,PR115,O114,OP15 17 | 2,PR116,O115,OP16 18 | 2,PR117,O116,OP17 19 | 2,PR118,O117,OP18 20 | 1,PR119,O118,OP19 21 | 4,PR120,O119,OP20 22 | 4,PR120,O120,OP21 23 | 4,PR120,O121,OP22 24 | 4,PR120,O122,OP23 25 | 4,PR124,O123,OP24 26 | 3,PR125,O124,OP25 27 | 3,PR126,O125,OP26 28 | 3,PR127,O126,OP27 29 | 3,PR128,O127,OP28 30 | 3,PR129,O128,OP29 31 | 5,PR130,O129,OP30 32 | 5,PR131,O130,OP31 33 | 5,PR132,O131,OP32 34 | 5,PR133,O132,OP33 35 | 5,PR134,O133,OP34 36 | 7,PR135,O134,OP35 37 | 5,PR136,O135,OP36 38 | 2,PR137,O136,OP37 39 | 2,PR138,O137,OP38 40 | 2,PR139,O138,OP39 41 | 2,PR140,O139,OP40 42 | 2,PR101,O140,OP41 43 | 2,PR101,O141,OP42 44 | 2,PR101,O142,OP43 45 | 2,PR101,O143,OP44 46 | 8,PR121,O144,OP45 47 | 4,PR121,O145,OP46 48 | 4,PR121,O146,OP47 49 | 4,PR121,O147,OP48 50 | 3,PR126,O148,OP49 51 | 3,PR127,O149,OP50 52 | 3,PR128,O150,OP51 53 | 6,PR109,O151,OP52 54 | 6,PR110,O152,OP53 55 | 6,PR111,O153,OP54 56 | 6,PR018,O154,OP55 57 | 3,PR019,O155,OP56 58 | 3,PR020,O156,OP57 59 | 3,PR021,O157,OP58 60 | 2,PR022,O158,OP59 61 | 2,PR023,O159,OP60 62 | 2,PR024,O160,OP61 63 | 2,PR025,O161,OP62 64 | 2,PR026,O162,OP63 65 | 5,PR027,O163,OP64 66 | 5,PR028,O164,OP65 67 | 5,PR029,O165,OP66 68 | 8,PR030,O166,OP67 69 | 8,PR031,O167,OP68 70 | 8,PR032,O168,OP69 71 | 9,PR033,O169,OP70 72 | 9,PR034,O170,OP71 73 | 9,PR035,O171,OP72 74 | 9,PR036,O172,OP73 75 | 9,PR037,O173,OP74 76 | 9,PR038,O174,OP75 77 | 9,PR039,O175,OP76 78 | 9,PR040,O176,OP77 79 | 9,PR041,O177,OP78 80 | 9,PR042,O178,OP79 81 | 9,PR043,O179,OP80 82 | 9,PR044,O180,OP81 83 | 9,PR045,O181,OP82 84 | 9,PR046,O182,OP83 85 | 9,PR047,O183,OP84 86 | 9,PR048,O184,OP85 87 | 9,PR049,O185,OP86 88 | 12,PR014,O186,OP87 89 | 12,PR015,O187,OP88 90 | 1,PR016,O178,OP89 91 | 1,PR017,O178,OP90 92 | 1,PR018,O178,OP91 93 | 1,PR019,O178,OP92 94 | 1,PR020,O178,OP93 95 | 1,PR021,O178,OP94 96 | 1,PR022,O178,OP95 97 | 1,PR033,O181,OP96 98 | 1,PR034,O182,OP97 99 | 1,PR035,O183,OP98 100 | 1,PR036,O184,OP99 101 | 1,PR037,O185,OP100 102 | 1,PR038,O186,OP101 103 | -------------------------------------------------------------------------------- /DBMS Retail Application/CSV Files/Customer.csv: -------------------------------------------------------------------------------- 1 | Customer_ID,First_Name,Last_Name,Phone_Number,Email_Address,Customer_Type 2 | 10000,kamala,Nayana,8576465699,nayana11@gmail.com,Student 3 | 10001,Nidhi,Mittal,8123457024,mittal11@gmail.com,Student 4 | 10002,Chandrika,Bolla,8123451709,bolla11@gmail.com,Student 5 | 10003,Gayathri,Maganti,8123546789,maganti11@gmail.com,Student 6 | 10004,Hithaishi,Avula,8987654321,avula11@gmail.com,Student 7 | 10005,Lahari,Palle,8120989767,palle1@gmail.com,Student 8 | 10006,Dheemanth,Uppalapati,8124366666,dhee11@gmail.com,Student 9 | 10007,Radha,Uppalapti,8127777777,ra11@gmail.com,Student 10 | 10008,Radha,Vallabhaneni,8177777772,radha11@gmail.com,Student 11 | 10009,Swarupa,kanaka,8777777712,swapu11@gmail.com,Student 12 | 10010,Anshika,Nunna,8101010102,anshi11@gmail.com,Student 13 | 10011,Avi,Pullela,8182818212,avi11@gmail.com,Student 14 | 10012,Keerthi,Kanakamedala,8272727212,keer11@gmail.com,Student 15 | 10013,Suresh,Kakarala,8292929212,suri11@gmail.com,Student 16 | 10014,Samba,Uppalapati,8129020932,samba11@gmail.com,Student 17 | 10015,Shruti,Ganji,8129302032,ganj11@gmail.com,Student 18 | 10016,Rahul,Samana,8116263742,sam11@gmail.com,Student 19 | 10017,Sindhu,Bhargavi,8199988892,sindh11@gmail.com,Student 20 | 10018,Harshith,Sahas,8190909092,harsh11@gmail.com,Student 21 | 10019,Sravya,Bobba,8909090912,srav11@gmail.com,Student 22 | 10020,Spoorthy,Kanamedala,8178787872,spoo11@gmail.com,Student 23 | 20000,Sita,Sree,8576460899,Sree11@gmail.com,Employee 24 | 20001,Nidhi,Mittal,8123456789,nm11@gmail.com,Employee 25 | 20002,Sandra,Meyer,8178780872,sandra00@gmail.com,Employee 26 | 20003,Laura,Meyer,8178780872,laura00@gmail.com,Employee 27 | 20004,Milly,George,8178780872,milly00@gmail.com,Employee 28 | 20005,Anna,Miller,8178780872,anna00@gmail.com,Employee 29 | 20006,Andy,Miller,8178780872,andy00@gmail.com,Employee 30 | 20007,Sandra,Bullock,8178780872,sandy00@gmail.com,Employee 31 | 20008,Stephne,Miller,8178780872,stephy00@gmail.com,Employee 32 | 20009,Lilly,Miller,8178780872,lilly00@gmail.com,Employee 33 | 20010,Roger,Mike,8178780872,roger00@gmail.com,Employee 34 | 20011,Andy,Blake,8178780872,blandy00@gmail.com,Employee 35 | 30000,John,Smith,8576400649,John11@gmail.com,Business 36 | 30001,Franklin,Roosevelt,987654321,roosevelt,Business 37 | 30002,Harry,Truman,987654312,harry123@gmail.com,Business 38 | 30003,Dwight,Eisenhower,987654313,Dwight@yahoo.com,Business 39 | 30004,John,Kennedy,987654314,Kennedy@yahoo.com,Business 40 | 30005,Lyndon,Johnson,987654315,Lyndon17@gmail.com,Business 41 | 30006,Richard,Nixon,987654361,nixon13@yahoo.com,Business 42 | 30007,Jimmy,Carter,987654317,carter12@yahoo.com,Business 43 | 30008,George,Bush,987654318,george@gmail.com,Business 44 | -------------------------------------------------------------------------------- /DBMS Retail Application/CSV Files/Customer Fix.csv: -------------------------------------------------------------------------------- 1 | Customer_ID,First_Name,Last_Name,Phone_Number,Email_Address,Customer_Type,Employee_ID 2 | 10000,kamala,Nayana,8576465699,nayana11@gmail.com,Student,E100 3 | 10001,Nidhi,Mittal,8123457024,mittal11@gmail.com,Student,E100 4 | 10002,Chandrika,Bolla,8123451709,bolla11@gmail.com,Student,E100 5 | 10003,Gayathri,Maganti,8123546789,maganti11@gmail.com,Student,E100 6 | 10004,Hithaishi,Avula,8987654321,avula11@gmail.com,Student,E106 7 | 10005,Lahari,Palle,8120989767,palle1@gmail.com,Student,E106 8 | 10006,Dheemanth,Uppalapati,8124366666,dhee11@gmail.com,Student,E106 9 | 10007,Radha,Uppalapti,8127777777,ra11@gmail.com,Student,E106 10 | 10008,Radha,Vallabhaneni,8177777772,radha11@gmail.com,Student,E106 11 | 10009,Swarupa,kanaka,8777777712,swapu11@gmail.com,Student,E106 12 | 10010,Anshika,Nunna,8101010102,anshi11@gmail.com,Student,E106 13 | 10011,Avi,Pullela,8182818212,avi11@gmail.com,Student,E107 14 | 10012,Keerthi,Kanakamedala,8272727212,keer11@gmail.com,Student,E107 15 | 10013,Suresh,Kakarala,8292929212,suri11@gmail.com,Student,E107 16 | 10014,Samba,Uppalapati,8129020932,samba11@gmail.com,Student,E112 17 | 10015,Shruti,Ganji,8129302032,ganj11@gmail.com,Student,E112 18 | 10016,Rahul,Samana,8116263742,sam11@gmail.com,Student,E112 19 | 10017,Sindhu,Bhargavi,8199988892,sindh11@gmail.com,Student,E112 20 | 10018,Harshith,Sahas,8190909092,harsh11@gmail.com,Student,E116 21 | 10019,Sravya,Bobba,8909090912,srav11@gmail.com,Student,E116 22 | 10020,Spoorthy,Kanamedala,8178787872,spoo11@gmail.com,Student,E116 23 | 20000,Sita,Sree,8576460899,Sree11@gmail.com,Employee,E120 24 | 20001,Nidhi,Mittal,8123456789,nm11@gmail.com,Employee,E120 25 | 20002,Sandra,Meyer,8178780872,sandra00@gmail.com,Employee,E120 26 | 20003,Laura,Meyer,8178780872,laura00@gmail.com,Employee,E120 27 | 20004,Milly,George,8178780872,milly00@gmail.com,Employee,E120 28 | 20005,Anna,Miller,8178780872,anna00@gmail.com,Employee,E119 29 | 20006,Andy,Miller,8178780872,andy00@gmail.com,Employee,E119 30 | 20007,Sandra,Bullock,8178780872,sandy00@gmail.com,Employee,E119 31 | 20008,Stephne,Miller,8178780872,stephy00@gmail.com,Employee,E109 32 | 20009,Lilly,Miller,8178780872,lilly00@gmail.com,Employee,E109 33 | 20010,Roger,Mike,8178780872,roger00@gmail.com,Employee,E109 34 | 20011,Andy,Blake,8178780872,blandy00@gmail.com,Employee,E118 35 | 30000,John,Smith,8576400649,John11@gmail.com,Business,E118 36 | 30001,Franklin,Roosevelt,987654321,roosevelt,Business,E118 37 | 30002,Harry,Truman,987654312,harry123@gmail.com,Business,E118 38 | 30003,Dwight,Eisenhower,987654313,Dwight@yahoo.com,Business,E118 39 | 30004,John,Kennedy,987654314,Kennedy@yahoo.com,Business,E118 40 | 30005,Lyndon,Johnson,987654315,Lyndon17@gmail.com,Business,E118 41 | 30006,Richard,Nixon,987654361,nixon13@yahoo.com,Business,E118 42 | 30007,Jimmy,Carter,987654317,carter12@yahoo.com,Business,E118 43 | 30008,George,Bush,987654318,george@gmail.com,Business,E118 44 | -------------------------------------------------------------------------------- /DBMS Retail Application/CSV Files/Orders.csv: -------------------------------------------------------------------------------- 1 | Order_ID,Order_Date,Status,Shippent_Duration,Payment_ID 2 | O100,3/22/2016,In Progress,Immediate,P10 3 | O101,11/15/2016,In Progress,Immediate,P11 4 | O102,8/23/2016,In Progress,Immediate,P12 5 | O103,2/18/2016,In Progress,Immediate,P13 6 | O104,9/10/2016,In Progress,Immediate,P14 7 | O105,5/24/2016,In Progress,Immediate,P15 8 | O106,4/3/2016,In Progress,Immediate,P16 9 | O107,7/10/2016,In Progress,Immediate,P17 10 | O108,11/8/2016,In Progress,Immediate,P18 11 | O109,7/21/2016,In Progress,Immediate,P19 12 | O110,10/27/2016,In Progress,Immediate,P20 13 | O111,5/6/2016,In Progress,Immediate,P21 14 | O112,4/21/2016,In Progress,Immediate,P22 15 | O113,8/20/2016,In Progress,Immediate,P23 16 | O114,4/14/2016,In Progress,Immediate,P24 17 | O115,4/2/2016,In Progress,Immediate,P25 18 | O116,10/31/2016,In Progress,Immediate,P26 19 | O117,7/4/2016,In Progress,Immediate,P27 20 | O118,4/19/2016,In Progress,Immediate,P28 21 | O119,5/1/2016,In Progress,With in 4 Days,P29 22 | O120,8/25/2016,In Progress,With in 4 Days,P30 23 | O121,1/17/2016,In Progress,With in 4 Days,P31 24 | O122,7/19/2016,In Progress,With in 4 Days,P32 25 | O123,5/21/2016,In Progress,With in 4 Days,P33 26 | O124,3/4/2016,In Progress,With in 4 Days,P34 27 | O125,11/6/2016,In Progress,With in 4 Days,P35 28 | O126,6/1/2016,In Progress,With in 4 Days,P36 29 | O127,5/18/2016,Shipped,With in 4 Days,P37 30 | O128,7/14/2016,Shipped,With in 4 Days,P38 31 | O129,8/25/2016,Shipped,With in 4 Days,P39 32 | O130,8/13/2016,Shipped,With in 4 Days,P40 33 | O131,12/26/2016,Shipped,With in 4 Days,P41 34 | O132,2/19/2016,Shipped,With in 4 Days,P42 35 | O133,1/20/2016,Shipped,With in 4 Days,P43 36 | O134,6/30/2016,Shipped,With in 4 Days,P44 37 | O135,2/12/2016,Shipped,With in 4 Days,P45 38 | O136,10/17/2016,Shipped,With in 4 Days,P46 39 | O137,7/18/2016,Shipped,With in 4 Days,P47 40 | O138,12/8/2016,Shipped,With in 4 Days,P48 41 | O139,6/11/2016,Shipped,With in 4 Days,P49 42 | O140,12/10/2016,Shipped,With in 4 Days,P50 43 | O141,10/7/2016,Shipped,With in 4 Days,P51 44 | O142,8/9/2016,Shipped,With in 4 Days,P52 45 | O143,10/22/2016,Shipped,With in 4 Days,P53 46 | O144,5/2/2016,Shipped,With in 4 Days,P54 47 | O145,12/23/2016,Shipped,With in 4 Days,P55 48 | O146,8/19/2016,Shipped,With in 4 Days,P56 49 | O147,12/17/2016,Shipped,With in 4 Days,P57 50 | O148,5/11/2016,Shipped,With in 4 Days,P58 51 | O149,6/27/2016,Shipped,With in 4 Days,P59 52 | O150,6/27/2016,Shipped,With in 4 Days,P60 53 | O151,4/14/2016,Shipped,With in 4 Days,P61 54 | O152,8/21/2016,Shipped,With in 4 Days,P62 55 | O153,6/14/2016,Shipped,With in 4 Days,P63 56 | O154,1/28/2016,Shipped,With in 4 Days,P64 57 | O155,6/8/2016,Shipped,With in 4 Days,P65 58 | O156,1/18/2016,Shipped,With in 4 Days,P66 59 | O157,6/24/2016,Shipped,With in 4 Days,P67 60 | O158,5/14/2016,Shipped,With in 1 Week,P68 61 | O159,12/9/2016,Shipped,With in 1 Week,P69 62 | O160,8/13/2016,Shipped,With in 1 Week,P70 63 | O161,3/19/2016,Shipped,With in 1 Week,P71 64 | O162,12/26/2016,Shipped,With in 1 Week,P72 65 | O163,9/27/2016,Shipped,With in 1 Week,P73 66 | O164,12/11/2016,Shipped,With in 1 Week,P74 67 | O165,7/21/2016,Shipped,With in 1 Week,P75 68 | O166,12/9/2016,Shipped,With in 1 Week,P76 69 | O167,3/10/2016,Shipped,With in 1 Week,P77 70 | O168,7/19/2016,Shipped,With in 1 Week,P78 71 | O169,8/9/2016,Shipped,With in 1 Week,P79 72 | O170,8/6/2016,Shipped,With in 1 Week,P80 73 | O171,6/8/2016,Shipped,With in 1 Week,P81 74 | O172,6/3/2016,Shipped,With in 1 Week,P82 75 | O173,4/29/2016,Partially Shipped,With in 1 Week,P83 76 | O174,4/17/2016,Partially Shipped,With in 1 Week,P84 77 | O175,7/27/2016,Partially Shipped,With in 1 Week,P85 78 | O176,7/7/2016,Partially Shipped,With in 1 Week,P86 79 | O177,9/8/2016,Partially Shipped,With in 1 Week,P87 80 | O178,5/4/2016,Partially Shipped,With in 1 Week,P88 81 | O179,1/20/2016,Partially Shipped,With in 1 Week,P89 82 | O180,7/20/2016,Partially Shipped,With in 1 Week,P90 83 | O181,8/3/2016,Partially Shipped,With in 1 Week,P91 84 | O182,7/25/2016,Partially Shipped,With in 1 Week,P92 85 | O183,4/23/2016,Partially Shipped,With in 1 Week,P93 86 | O184,11/27/2016,Partially Shipped,With in 1 Week,P94 87 | O185,12/17/2016,Partially Shipped,With in 1 Week,P95 88 | O186,1/24/2016,Partially Shipped,With in 1 Week,P96 89 | O187,3/4/2016,Partially Shipped,With in 1 Week,P97 90 | -------------------------------------------------------------------------------- /DBMS Retail Application/CSV Files/order.csv: -------------------------------------------------------------------------------- 1 | Order_ID,Order_Date,Status,Shippent_Duration,Payment_ID 2 | O100,2/19/2016,In Progress,Immediate,P10 3 | O101,7/25/2016,In Progress,Immediate,P11 4 | O102,7/17/2016,In Progress,Immediate,P12 5 | O103,4/29/2016,In Progress,Immediate,P13 6 | O104,8/16/2016,In Progress,Immediate,P14 7 | O105,2/7/2016,In Progress,Immediate,P15 8 | O106,4/7/2016,In Progress,Immediate,P16 9 | O107,12/29/2016,In Progress,Immediate,P17 10 | O108,2/5/2016,In Progress,Immediate,P18 11 | O109,11/29/2016,In Progress,Immediate,P19 12 | O110,12/29/2016,In Progress,Immediate,P20 13 | O111,7/31/2016,In Progress,Immediate,P21 14 | O112,5/23/2016,In Progress,Immediate,P22 15 | O113,8/21/2016,In Progress,Immediate,P23 16 | O114,8/2/2016,In Progress,Immediate,P24 17 | O115,5/10/2016,In Progress,Immediate,P25 18 | O116,10/27/2016,In Progress,Immediate,P26 19 | O117,12/18/2016,In Progress,Immediate,P27 20 | O118,6/17/2016,In Progress,Immediate,P28 21 | O119,8/22/2016,In Progress,With in 4 Days,P29 22 | O120,11/9/2016,In Progress,With in 4 Days,P30 23 | O121,10/16/2016,In Progress,With in 4 Days,P31 24 | O122,12/21/2016,In Progress,With in 4 Days,P32 25 | O123,3/9/2016,In Progress,With in 4 Days,P33 26 | O124,4/12/2016,In Progress,With in 4 Days,P34 27 | O125,1/15/2016,In Progress,With in 4 Days,P35 28 | O126,7/9/2016,In Progress,With in 4 Days,P36 29 | O127,12/15/2016,Shipped,With in 4 Days,P37 30 | O128,7/18/2016,Shipped,With in 4 Days,P38 31 | O129,3/13/2016,Shipped,With in 4 Days,P39 32 | O130,6/12/2016,Shipped,With in 4 Days,P40 33 | O131,3/26/2016,Shipped,With in 4 Days,P41 34 | O132,4/23/2016,Shipped,With in 4 Days,P42 35 | O133,9/19/2016,Shipped,With in 4 Days,P43 36 | O134,6/25/2016,Shipped,With in 4 Days,P44 37 | O135,2/29/2016,Shipped,With in 4 Days,P45 38 | O136,8/24/2016,Shipped,With in 4 Days,P46 39 | O137,7/30/2016,Shipped,With in 4 Days,P47 40 | O138,10/21/2016,Shipped,With in 4 Days,P48 41 | O139,3/7/2016,Shipped,With in 4 Days,P49 42 | O140,5/16/2016,Shipped,With in 4 Days,P50 43 | O141,6/3/2016,Shipped,With in 4 Days,P51 44 | O142,2/2/2016,Shipped,With in 4 Days,P52 45 | O143,1/11/2016,Shipped,With in 4 Days,P53 46 | O144,5/31/2016,Shipped,With in 4 Days,P54 47 | O145,2/29/2016,Shipped,With in 4 Days,P55 48 | O146,11/2/2016,Shipped,With in 4 Days,P56 49 | O147,12/26/2016,Shipped,With in 4 Days,P57 50 | O148,11/13/2016,Shipped,With in 4 Days,P58 51 | O149,12/27/2016,Shipped,With in 4 Days,P59 52 | O150,1/19/2016,Shipped,With in 4 Days,P60 53 | O151,4/8/2016,Shipped,With in 4 Days,P61 54 | O152,12/9/2016,Shipped,With in 4 Days,P62 55 | O153,10/27/2016,Shipped,With in 4 Days,P63 56 | O154,12/6/2016,Shipped,With in 4 Days,P64 57 | O155,11/28/2016,Shipped,With in 4 Days,P65 58 | O156,10/11/2016,Shipped,With in 4 Days,P66 59 | O157,2/4/2016,Shipped,With in 4 Days,P67 60 | O158,9/26/2016,Shipped,With in 1 Week,P68 61 | O159,3/9/2016,Shipped,With in 1 Week,P69 62 | O160,12/30/2016,Shipped,With in 1 Week,P70 63 | O161,11/16/2016,Shipped,With in 1 Week,P71 64 | O162,1/13/2016,Shipped,With in 1 Week,P72 65 | O163,8/24/2016,Shipped,With in 1 Week,P73 66 | O164,6/23/2016,Shipped,With in 1 Week,P74 67 | O165,9/14/2016,Shipped,With in 1 Week,P75 68 | O166,8/10/2016,Shipped,With in 1 Week,P76 69 | O167,11/20/2016,Shipped,With in 1 Week,P77 70 | O168,4/11/2016,Shipped,With in 1 Week,P78 71 | O169,11/27/2016,Shipped,With in 1 Week,P79 72 | O170,4/9/2016,Shipped,With in 1 Week,P80 73 | O171,6/23/2016,Shipped,With in 1 Week,P81 74 | O172,8/17/2016,Shipped,With in 1 Week,P82 75 | O173,8/9/2016,Partially Shipped,With in 1 Week,P83 76 | O174,7/15/2016,Partially Shipped,With in 1 Week,P84 77 | O175,7/28/2016,Partially Shipped,With in 1 Week,P85 78 | O176,2/21/2016,Partially Shipped,With in 1 Week,P86 79 | O177,8/3/2016,Partially Shipped,With in 1 Week,P87 80 | O178,2/21/2016,Partially Shipped,With in 1 Week,P88 81 | O179,10/21/2016,Partially Shipped,With in 1 Week,P89 82 | O180,5/7/2016,Partially Shipped,With in 1 Week,P90 83 | O181,6/23/2016,Partially Shipped,With in 1 Week,P91 84 | O182,3/24/2016,Partially Shipped,With in 1 Week,P92 85 | O183,3/20/2016,Partially Shipped,With in 1 Week,P93 86 | O184,7/14/2016,Partially Shipped,With in 1 Week,P94 87 | O185,2/13/2016,Partially Shipped,With in 1 Week,P95 88 | O186,12/17/2016,Partially Shipped,With in 1 Week,P96 89 | O187,12/14/2016,Partially Shipped,With in 1 Week,P97 90 | -------------------------------------------------------------------------------- /DBMS Retail Application/README.md: -------------------------------------------------------------------------------- 1 | # Database Management for Retail Application 2 | ### Problem Statement: 3 | * A Retail business organization (target) is not able to handle and maintain the details of potential market. 4 | * It is unable to manage various employees who belong to various departments, information about the customers and sold products their defects, quality and Voucher details etc. 5 | ### Scope of Project: 6 | * This project aims to build a database for retail application for an organization like Target where customers buy projects online and offline. 7 | * Retail application database is mainly used by the retail store administrators to improve their sales by analyze the product sales, customer and employees working in their organization 8 | * This project helps in designing unique database which holds the information of the business model to properly store, analyze the data that company is looking for 9 | * Products list with minimum defects and maximum quality can be know which helps the organization to maintain good quality products in their store and increase their sales 10 | * This project helps the organization to store and analyze customers, employee, product sales details. 11 | * This Database design helps in analyzing which product is highly rated by customers, Total revenue earned by online and offline payment modes. 12 | ### Identification of Entities: 13 | * Employee 14 | * Customer 15 | * Address 16 | * Zip Code 17 | * Bill 18 | * Payment Mode 19 | * Order 20 | * Order Item 21 | * Order Product 22 | * Product 23 | * Voucher 24 | * Product Group 25 | * Product Description 26 | * Reviews 27 | 28 | ⇾ Employee-Any person who is employed as a part of company staff 29 | Attributes: EmployeeID, EmpFirst_Name, EmpLast_SSN, EmpMail_Address, Designation, Department, Salary, Employee_Type. 30 | 31 | ⇾ Customer -A person who buys products with cash or card basis. He may be internal or external customer. 32 | Attributes: CustomerID, First_Name, Last_Name, Mail_Address, Phone_Number, Category 33 | 34 | ⇾ Bill -Bill includes the total bill for the purchased products and amount that customer paid 35 | Attributes: Billing_ID, Amount_Paid 36 | 37 | ⇾ Address -Address to with a particular order must be delivered. 38 | Attributes: AddressID, Address_line1, Address_line2 39 | 40 | ⇾ Zip Code -Zip details of customers address is included 41 | Attributes: ZipCode, City, State 42 | 43 | ⇾ Payment- This table hold Date of customer visit number, payment and payment type whether the customer bought directly from store or purchased online. It also includes the customer card details 44 | Attributes: Payment_ID, Payment_Type, CreditCard_Number,Card_Type, CVV_Number, ExpiryDate, CardHolder_Name 45 | 46 | ⇾ Orders – This table hold the status of the order whether the order is delivered or not and the shipment option given by the customer. 47 | Attributes: Order_ID,Shippment_Duration, Order_Date,Status. 48 | 49 | ⇾ Order Item-OrderItem contains the details like date and quantity of items purchased. 50 | Attributes: Date of Order, Quantity 51 | 52 | ⇾ Order Product- This contains the details of quantity of product that customer ordered 53 | Attributes: OrderProduct_ID, Quantity 54 | 55 | ⇾ Voucher- Voucher includes priority of customers so based on that customers are given discount on their purchase. 56 | Attributes: Voucher_Number, Description, Priority, Quantity_Item 57 | 58 | ⇾ Product -It is a form of good that is purchased by customer. 59 | Attributes: ProductID, Product_Name, Available_Number 60 | 61 | ⇾ Product Details – Product details contains the description of particular product 62 | Attributes: Weight, Width, Colour, Height 63 | 64 | ⇾ Product Group – Product group tells to which category the product belongs to (Ex. Electronics) 65 | Attributes: Group_ID, Group_Name 66 | 67 | ⇾ Review-Reviews are the feedback given to the product by customers. 68 | Attributes: Quality, Defect%, Review_ID, Review_Date 69 | 70 | ### ER Diagram for Retail Application 71 | #### ER Diagram for Retail Application Before Normalization: 72 | ![111](https://user-images.githubusercontent.com/25045759/27304876-866e2f90-550d-11e7-944a-695b7d39b45a.jpg) 73 | ![222](https://user-images.githubusercontent.com/25045759/27304877-86769478-550d-11e7-9e25-878464cf6d56.jpg) 74 | 75 | #### After Normalization 76 | ![333](https://user-images.githubusercontent.com/25045759/27304878-8679f712-550d-11e7-8dd3-d2ad92ee5289.jpg) 77 | 78 | -------------------------------------------------------------------------------- /DBMS Retail Application/CSV Files/Employee New.csv: -------------------------------------------------------------------------------- 1 | Payment_ID,Payment_Mode,Card_Type,Card_Number,CVV,Name_On_Card,Customer_ID,Visit_Number,Employee_ID 2 | P10,online,credit,2637231147,259,Tom,10001,1,E100 3 | P11,online,debit,2314090152,628,Robert,10002,1,E100 4 | P12,online,debit,3160466116,750,Sandra,10002,2,E100 5 | P13,online,debit,1924770950,643,Meyer,10002,3,E100 6 | P14,online,debit,2605710031,348,Laura,10002,4,E100 7 | P15,online,debit,1760861438,372,Paul,10002,5,E101 8 | P16,online,debit,2486382462,821,Stephen,10002,6,E101 9 | P17,online,debit,2026172246,573,Richard,10002,7,E102 10 | P18,online,debit,1652325458,664,Danie,10002,8,E102 11 | P19,online,debit,1593155579,527,Danie,10003,1,E104 12 | P20,online,debit,3600749836,366,Danie,10003,2,E104 13 | P21,online,debit,1629603244,331,Danie,10003,3,E104 14 | P22,online,credit,2196257042,497,Danie,10003,4,E104 15 | P23,online,credit,3176037606,699,Danie,10003,5,E104 16 | P24,online,credit,4227850650,867,Danie,10003,6,E104 17 | P25,online,credit,1922366282,870,Danie,10005,1,E104 18 | P26,online,credit,4290419995,890,Danie,10006,1,E104 19 | P27,online,credit,1831996471,268,Paul,10006,2,E104 20 | P28,online,credit,2394100413,417,Paul,10006,3,E104 21 | P29,online,credit,1127802595,488,Paul,10006,4,E115 22 | P30,online,credit,3211572399,599,Paul,10006,5,E115 23 | P31,online,credit,3754477702,376,Paul,10007,1,E115 24 | P32,online,credit,4332207305,283,Paul,10007,2,E115 25 | P33,online,credit,1370698763,642,Paul,10007,3,E115 26 | P34,online,credit,3046243391,150,Paul,10007,4,E115 27 | P35,online,debit,2145277261,644,Paul,10007,5,E115 28 | P36,online,debit,1427358687,815,Paul,10007,6,E115 29 | P37,online,debit,3879003240,704,Paul,10007,7,E115 30 | P38,online,debit,1494504380,518,Mike,10007,8,E115 31 | P39,online,debit,1513724846,471,Mike,10007,9,E115 32 | P40,online,debit,1150749080,659,Mike,10007,10,E115 33 | P41,online,debit,2021084797,490,Mike,10008,1,E115 34 | P42,online,debit,2583687271,846,Mike,10008,2,E115 35 | P43,online,debit,2643425696,265,Mike,10008,3,E115 36 | P44,direct,debit,1627922960,258,Mike,10009,1,E116 37 | P45,direct,debit,3349298033,660,Mike,10009,2,E116 38 | P46,direct,debit,2556226002,517,Mike,10009,3,E116 39 | P47,direct,debit,2122858396,441,Mike,10009,4,E116 40 | P48,direct,debit,4327209833,326,Mike,10009,5,E116 41 | P49,direct,credit,3216903325,487,Mike,10009,6,E116 42 | P50,direct,credit,1819229414,813,Mike,10009,7,E116 43 | P51,direct,credit,2751033800,882,Mike,10009,8,E117 44 | P52,direct,credit,1641183774,308,Mike,10009,9,E116 45 | P53,direct,credit,1194550010,350,Mike,10010,1,E117 46 | P54,direct,credit,1408194222,377,Esteller,10010,2,E117 47 | P55,direct,credit,1342371996,318,Esteller,10010,3,E117 48 | P56,direct,credit,3259865998,562,Esteller,10010,4,E117 49 | P57,direct,credit,4198907218,691,Esteller,10010,5,E117 50 | P58,direct,credit,1253548883,134,Esteller,10011,1,E117 51 | P59,direct,credit,2769503830,288,Esteller,10012,1,E117 52 | P60,direct,credit,4111052432,774,Esteller,10013,1,E119 53 | P61,direct,credit,2733430220,310,Esteller,10014,1,E119 54 | P62,direct,credit,1481583127,206,Esteller,10015,1,E118 55 | P63,direct,credit,1754015666,590,Esteller,10016,1,E118 56 | P64,direct,credit,4327697062,143,Esteller,10017,1,E108 57 | P65,direct,credit,2776996454,445,Esteller,10018,1,E108 58 | P66,direct,credit,1508118285,102,Esteller,10019,1,E108 59 | P67,direct,credit,3613558356,618,Sandra,10020,1,E108 60 | P68,direct,credit,1377075209,387,Sandra,20000,1,E108 61 | P69,direct,credit,1775034267,308,Sandra,20001,1,E108 62 | P70,direct,credit,1086781067,817,Sandra,20002,1,E108 63 | P71,direct,credit,4289402597,398,Sandra,20003,1,E108 64 | P72,direct,credit,1867595319,166,Sandra,20004,1,E108 65 | P73,direct,credit,2153326098,334,Sandra,20005,1,E108 66 | P74,direct,credit,2287425122,767,Sandra,20006,1,E112 67 | P75,direct,credit,3153569739,796,Sandra,20007,1,E112 68 | P76,direct,credit,2907204337,378,Sandra,20008,1,E112 69 | P77,direct,credit,3379971129,610,Adam,20009,1,E112 70 | P78,direct,credit,3559421590,516,Adam,20010,1,E112 71 | P79,direct,credit,4068575013,848,Adam,20011,1,E113 72 | P89,direct,credit,2740985596,114,Robert,30000,1,E113 73 | P90,direct,credit,4209354840,880,Robert,30001,1,E113 74 | P91,direct,credit,1903101101,552,Robert,30002,1,E113 75 | P92,direct,credit,1022378637,861,Robert,30003,1,E114 76 | P93,direct,credit,3940621897,596,Robert,30004,1,E114 77 | P94,direct,credit,1793626701,885,Robert,30005,1,E114 78 | P95,direct,credit,1936844809,677,Robert,30006,1,E114 79 | P96,direct,credit,1121240227,433,Robert,30007,1,E114 80 | P97,direct,credit,4160078849,842,Robert,30008,1,E114 81 | -------------------------------------------------------------------------------- /DBMS Retail Application/CSV Files/Payment.csv: -------------------------------------------------------------------------------- 1 | Payment_ID,Payment_Mode,Card_Type,Card_Number,CVV,Name_On_Card,Customer_ID,Visit_Number 2 | P10,online,credit,2637231147,259,Tom,10001,1 3 | P11,online,debit,2314090152,628,Robert,10002,1 4 | P12,online,debit,3160466116,750,Sandra,10002,2 5 | P13,online,debit,1924770950,643,Meyer,10002,3 6 | P14,online,debit,2605710031,348,Laura,10002,4 7 | P15,online,debit,1760861438,372,Paul,10002,5 8 | P16,online,debit,2486382462,821,Stephen,10002,6 9 | P17,online,debit,2026172246,573,Richard,10002,7 10 | P18,online,debit,1652325458,664,Danie,10002,8 11 | P19,online,debit,1593155579,527,Danie,10003,1 12 | P20,online,debit,3600749836,366,Danie,10003,2 13 | P21,online,debit,1629603244,331,Danie,10003,3 14 | P22,online,credit,2196257042,497,Danie,10003,4 15 | P23,online,credit,3176037606,699,Danie,10003,5 16 | P24,online,credit,4227850650,867,Danie,10003,6 17 | P25,online,credit,1922366282,870,Danie,10005,1 18 | P26,online,credit,4290419995,890,Danie,10006,1 19 | P27,online,credit,1831996471,268,Paul,10006,2 20 | P28,online,credit,2394100413,417,Paul,10006,3 21 | P29,online,credit,1127802595,488,Paul,10006,4 22 | P30,online,credit,3211572399,599,Paul,10006,5 23 | P31,online,credit,3754477702,376,Paul,10007,1 24 | P32,online,credit,4332207305,283,Paul,10007,2 25 | P33,online,credit,1370698763,642,Paul,10007,3 26 | P34,online,credit,3046243391,150,Paul,10007,4 27 | P35,online,debit,2145277261,644,Paul,10007,5 28 | P36,online,debit,1427358687,815,Paul,10007,6 29 | P37,online,debit,3879003240,704,Paul,10007,7 30 | P38,online,debit,1494504380,518,Mike,10007,8 31 | P39,online,debit,1513724846,471,Mike,10007,9 32 | P40,online,debit,1150749080,659,Mike,10007,10 33 | P41,online,debit,2021084797,490,Mike,10008,1 34 | P42,online,debit,2583687271,846,Mike,10008,2 35 | P43,online,debit,2643425696,265,Mike,10008,3 36 | P44,direct,debit,1627922960,258,Mike,10009,1 37 | P45,direct,debit,3349298033,660,Mike,10009,2 38 | P46,direct,debit,2556226002,517,Mike,10009,3 39 | P47,direct,debit,2122858396,441,Mike,10009,4 40 | P48,direct,debit,4327209833,326,Mike,10009,5 41 | P49,direct,credit,3216903325,487,Mike,10009,6 42 | P50,direct,credit,1819229414,813,Mike,10009,7 43 | P51,direct,credit,2751033800,882,Mike,10009,8 44 | P52,direct,credit,1641183774,308,Mike,10009,9 45 | P53,direct,credit,1194550010,350,Mike,10010,1 46 | P54,direct,credit,1408194222,377,Esteller,10010,2 47 | P55,direct,credit,1342371996,318,Esteller,10010,3 48 | P56,direct,credit,3259865998,562,Esteller,10010,4 49 | P57,direct,credit,4198907218,691,Esteller,10010,5 50 | P58,direct,credit,1253548883,134,Esteller,10011,1 51 | P59,direct,credit,2769503830,288,Esteller,10012,1 52 | P60,direct,credit,4111052432,774,Esteller,10013,1 53 | P61,direct,credit,2733430220,310,Esteller,10014,1 54 | P62,direct,credit,1481583127,206,Esteller,10015,1 55 | P63,direct,credit,1754015666,590,Esteller,10016,1 56 | P64,direct,credit,4327697062,143,Esteller,10017,1 57 | P65,direct,credit,2776996454,445,Esteller,10018,1 58 | P66,direct,credit,1508118285,102,Esteller,10019,1 59 | P67,direct,credit,3613558356,618,Sandra,10020,1 60 | P68,direct,credit,1377075209,387,Sandra,20000,1 61 | P69,direct,credit,1775034267,308,Sandra,20001,1 62 | P70,direct,credit,1086781067,817,Sandra,20002,1 63 | P71,direct,credit,4289402597,398,Sandra,20003,1 64 | P72,direct,credit,1867595319,166,Sandra,20004,1 65 | P73,direct,credit,2153326098,334,Sandra,20005,1 66 | P74,direct,credit,2287425122,767,Sandra,20006,1 67 | P75,direct,credit,3153569739,796,Sandra,20007,1 68 | P76,direct,credit,2907204337,378,Sandra,20008,1 69 | P77,direct,credit,3379971129,610,Adam,20009,1 70 | P78,direct,credit,3559421590,516,Adam,20010,1 71 | P79,direct,credit,4068575013,848,Adam,20011,1 72 | P80,direct,credit,1461189748,684,Adam,20012,1 73 | P81,direct,credit,1603218647,441,Adam,20013,1 74 | P82,direct,credit,3698423753,448,Adam,20014,1 75 | P83,direct,credit,4352973259,652,Adam,20015,1 76 | P84,direct,credit,2060023961,848,Adam,20016,1 77 | P85,direct,credit,1490287836,319,Robert,20017,1 78 | P86,direct,credit,1528160762,455,Robert,20018,1 79 | P87,direct,credit,2465051294,269,Robert,20019,1 80 | P88,direct,credit,1725024863,837,Robert,20020,1 81 | P89,direct,credit,2740985596,114,Robert,30000,1 82 | P90,direct,credit,4209354840,880,Robert,30001,1 83 | P91,direct,credit,1903101101,552,Robert,30002,1 84 | P92,direct,credit,1022378637,861,Robert,30003,1 85 | P93,direct,credit,3940621897,596,Robert,30004,1 86 | P94,direct,credit,1793626701,885,Robert,30005,1 87 | P95,direct,credit,1936844809,677,Robert,30006,1 88 | P96,direct,credit,1121240227,433,Robert,30007,1 89 | P97,direct,credit,4160078849,842,Robert,30008,1 90 | -------------------------------------------------------------------------------- /DBMS Retail Application/SQLQueries,Triggers,StoredProcedures,Views.sql: -------------------------------------------------------------------------------- 1 | --QUERIES 2 | ____________________________________________________________________________________________________________________________________________________________________ 3 | --Query1 4 | --Find how many customers are there group by category 5 | 6 | SELECT Customer_Type, count(Customer_Type) as Total 7 | FROM anra.customer 8 | GROUP BY Customer_Type; 9 | 10 | --Query2 11 | --Find 2 appartments whose name is emerald or their id is 11003 12 | SELECT Address_ID, Appartment_Name, Zipcode_ID 13 | FROM anra.address 14 | WHERE (Appartment_Name= 'Emerald' OR Zipcode_ID = '11003') 15 | ORDER BY Zipcode_ID DESC 16 | Limit 2; 17 | 18 | --Query3 19 | --Find the supplied product count and their group for each product 20 | 21 | select anra.supplier.Supplier_ID,anra.supplier.Supplier_Name, Count(anra.product.Group_ID) AS `Product Count`, anra.`product group`.Group_Name 22 | from 23 | anra.supplier 24 | inner join 25 | anra.product 26 | on anra.supplier.Supplier_ID=anra.product.Supplier_ID 27 | inner join 28 | anra.`product group` 29 | on anra.product.Group_ID=anra.`product group`.Group_ID 30 | 31 | Group by Supplier_ID Asc 32 | 33 | --Query4 34 | --Total number of orders to be shipped immediate and is partially Shipped 35 | 36 | SELECT Order_ID, Order_Date,`Status`,count(Order_ID) as Total 37 | FROM anra.orders 38 | WHERE (Shippent_Duration= 'Immediate' and`Status`='Partially Shipped') 39 | ORDER BY Order_ID DESC; 40 | 41 | --Query5 42 | --List of products by department which has high defect% 43 | 44 | SELECT anra.reviews.Product_ID,anra.product.Product_Name, 45 | MAX(anra.reviews.`Defect%`) As `Defect%`, anra.`product group`.Group_Name 46 | from 47 | anra.reviews 48 | inner join 49 | anra.product 50 | on anra.reviews.Product_ID=anra.product.Product_ID 51 | inner join 52 | anra.`product group` 53 | on anra.product.Group_ID=anra.`product group`.Group_ID 54 | Group by `product group`.Group_ID 55 | 56 | --Query6 57 | --Total amount of revenue earned with respect to their purchasing modes 58 | 59 | Select count(Payment_Mode) As Total_Cutomers, anra.payment.Payment_Mode,Sum(anra.bill.Amount_Paid) 60 | As Total_Amount 61 | from anra.payment 62 | inner join 63 | anra.bill 64 | on anra.payment.Payment_ID=anra.bill.Payment_ID 65 | group by Payment_Mode 66 | 67 | 68 | 69 | --Query7 70 | --Find The quantity of products available whose status is in progress and shipment duration is immediate 71 | 72 | 73 | SELECT anra.product.Product_Name,anra.product.Available_Number,`order product`.Quantity,orders.Order_Date, orders.`Status`,orders.Shippent_Duration 74 | from 75 | anra.orders 76 | inner join 77 | anra.`order product` 78 | on anra.orders.Order_ID=anra.`order product`.Order_ID 79 | inner join 80 | anra.product 81 | on anra.`order product`.Product_ID=anra.product.Product_ID 82 | where 83 | orders.`Status`='In Progress' and orders.Shippent_Duration='Immediate'; 84 | 85 | --Query8 86 | --Find the names and defect% order by defect% 87 | SELECT Product_Name,`Defect%` 88 | FROM anra.product 89 | INNER JOIN anra.reviews 90 | ON anra.reviews.Product_ID=anra.product.Product_ID 91 | ORDER BY `Defect%` Desc; 92 | 93 | --Query9 94 | --Find Customers payment ID,mode, vocher applied and their visist number 95 | SELECT anra.bill.Voucher_id, anra.payment.Payment_ID, anra.payment.Payment_Mode, anra.payment.Visit_Number 96 | FROM anra.bill,anra.payment 97 | WHERE anra.payment.Payment_ID=anra.bill.Payment_ID 98 | AND anra.bill.Amount_Paid> 1000; 99 | 100 | --Query10 101 | --Find product and their respective colour 102 | SELECT Product_Name, Colour 103 | FROM anra.`product details` 104 | INNER JOIN anra.product 105 | ON anra.`product details`.Product_ID=anra.product.Product_ID order by colour 106 | 107 | --Query11 108 | --Find the product Names their respective groups 109 | SELECT 110 | Group_Name, Product_Name 111 | FROM anra.`product group` 112 | INNER JOIN anra.product 113 | ON anra.`product group`.Group_ID=anra.product.Group_ID Order by Group_Name 114 | 115 | 116 | 117 | 118 | --TRIGGERS 119 | _________________________________________________________________________________________________________________________________________________ 120 | --Trigger1 121 | --Find Customer name and updated time on customers table 122 | create table 123 | UpdateCustomerDetails 124 | (Customer_id int, First_Name varchar(20), update_time Datetime) 125 | 126 | 127 | delimiter \\ 128 | create trigger UpdateCustomerDetails_trigger 129 | after update on customer 130 | for each row 131 | begin 132 | declare new_date datetime; 133 | set new_date=now(); 134 | 135 | insert into UpdateCustomerDetails(Customer_id,First_Name,update_time) 136 | values(old.Customer_ID,old.First_Name, new_date); 137 | 138 | end \\ 139 | 140 | --when customers details are updated the trigger is set 141 | update customer set Email_Address='naynaa@gmail.com' 142 | where Customer_ID=10000 143 | 144 | --updates can be seen in the newly created table 145 | select * from UpdateCustomerDetails 146 | 147 | 148 | 149 | --Trigger2 150 | --Trigger3 151 | --Trigger4 152 | 153 | --Stored_Procedure 154 | _______________________________________________________________________________________________________________________________________________ 155 | --1 156 | --Stored procedure to find most deffective product from each product group 157 | call GetMostDeffective_Product() 158 | 159 | delimiter// 160 | Create Procedure GetMostDeffective_Product() 161 | Begin 162 | SELECT anra.reviews.Product_ID,anra.product.Product_Name,MAX(anra.reviews.`Defect%`) As `Defect%`, anra.`product group`.Group_Name 163 | from 164 | anra.reviews 165 | inner join 166 | anra.product 167 | on anra.reviews.Product_ID=anra.product.Product_ID 168 | inner join 169 | anra.`product group` 170 | on anra.product.Group_ID=anra.`product group`.Group_ID 171 | Group by `product group`.Group_Name 172 | end// 173 | 174 | --2 175 | --Stored procedure for employee assesment 176 | call GetEmployee_Assesment () 177 | 178 | delimiter// 179 | Create Procedure GetEmployee_Assesment () 180 | Begin 181 | Select count(anra.customer.Customer_ID) as Total_Cutomers ,anra.customer.Employee_ID,anra.employee.Designation,Salary 182 | from anra.customer 183 | Inner Join 184 | anra.employee 185 | on 186 | anra.employee.Employee_ID=anra.customer.Employee_ID 187 | group by Employee_ID 188 | order by count(anra.customer.Customer_ID) ; 189 | end// 190 | 191 | --3 192 | --Stored procedure to find customer details of highest Amount_Paid 193 | call findMaxBill() 194 | 195 | delimiter// 196 | Create Procedure findMaxBill() 197 | Begin 198 | select Max(anra.bill.Amount_Paid) As GreatestPurchase, anra.customer.Customer_ID,anra.customer.First_Name from anra.bill 199 | inner join 200 | anra.payment 201 | on anra.payment.Payment_ID=anra.bill.Payment_ID 202 | inner join 203 | anra.Customer 204 | on anra.payment.Customer_ID=anra.customer.Customer_ID; 205 | end// 206 | 207 | --Views 208 | ___________________________________________________________________________________________________________________________________________ 209 | --1 210 | --Student as customer views 211 | 212 | create view StudentAsCustomer as ( select * from customer where Customer_Type = 'Student') 213 | 214 | --2 215 | --Product details with minimum defect% and high rating 216 | create view LeastDefectHighRating as 217 | (select product.Product_Name, min(reviews.`Defect%`), max(reviews.Quality_Rating) 218 | from anra.reviews 219 | inner join 220 | anra.product 221 | on anra.reviews.Product_ID=anra.product.Product_ID) 222 | 223 | 224 | --3 225 | --Products and the colours available 226 | create view ProductandAvailableColours as 227 | (SELECT Product_Name, Colour 228 | FROM anra.`product details` 229 | INNER JOIN anra.product 230 | ON anra.`product details`.Product_ID=anra.product.Product_ID order by colour) 231 | 232 | 233 | --4 234 | --Distinct employee departments whose salary is greater than 1200 limit to 4 235 | create view DistinctEmployeeDepartments as 236 | (Select DISTINCT anra.employee.Designation,anra.employee.Employee_Name,anra.employee.Department 237 | From anra.employee 238 | Where anra.employee.salary>1200 limit 4) 239 | 240 | --5 241 | -- 242 | Create view TotalAmount as Total amount of revenue earned with respect to their purchasing modes 243 | (Select count(Payment_Mode) As Total_Cutomers, anra.payment.Payment_Mode,Sum(anra.bill.Amount_Paid) 244 | As Total_Amount 245 | from anra.payment 246 | inner join 247 | anra.bill 248 | on anra.payment.Payment_ID=anra.bill.Payment_ID 249 | group by Payment_Mode) 250 | 251 | 252 | --6 253 | Select count(anra.customer.Customer_ID) as Total_Customers, anra.customer.Emploee_ID,anra.emploee.Designation 254 | From anra.customer 255 | Inner Join 256 | anra.employee 257 | on anra.employee.Employee_ID=anra.customer.Employee_ID 258 | group by Employee_ID 259 | order by count(anra.customers.Customer_ID) desc 260 | 261 | --7 262 | --View Salary of employee group by type and department 263 | create view SalaryGroupbyType as 264 | (Select Salary, Employee_Type,Department 265 | From anra.employee 266 | Group by Employee_Type,Department) 267 | 268 | 269 | 270 | 271 | 272 | 273 | 274 | 275 | 276 | 277 | 278 | 279 | 280 | 281 | 282 | 283 | 284 | 285 | 286 | 287 | 288 | 289 | 290 | 291 | 292 | 293 | 294 | 295 | 296 | -------------------------------------------------------------------------------- /DBMS Retail Application/SQL/Generated.SQL: -------------------------------------------------------------------------------- 1 | /* 2 | Created: 12/1/2016 3 | Modified: 12/6/2016 4 | Model: MySQL 5.7 5 | Database: MySQL 5.7 6 | */ 7 | 8 | 9 | -- Create tables section ------------------------------------------------- 10 | 11 | -- Table Employee 12 | 13 | CREATE TABLE `Employee` 14 | ( 15 | `Designation` Varchar(20), 16 | `Department` Varchar(20), 17 | `Join_Date` Date, 18 | `ssn` Int(9) NOT NULL 19 | ) 20 | ; 21 | 22 | CREATE INDEX `IX_Relationship30` ON `Employee` (`ssn`) 23 | ; 24 | 25 | ALTER TABLE `Employee` ADD PRIMARY KEY (`ssn`) 26 | ; 27 | 28 | -- Table Person 29 | 30 | CREATE TABLE `Person` 31 | ( 32 | `First_Name` Varchar(20), 33 | `Last_Name` Varchar(20), 34 | `Email_Address` Varchar(20), 35 | `Phone_Number` Int(10), 36 | `ssn` Int(9) NOT NULL, 37 | `Date_Of_Birth` Date 38 | ) 39 | ; 40 | 41 | ALTER TABLE `Person` ADD PRIMARY KEY (`ssn`) 42 | ; 43 | 44 | -- Table Orders 45 | 46 | CREATE TABLE `Orders` 47 | ( 48 | `Order_ID` Char(4) NOT NULL, 49 | `Order_Date` Date NOT NULL, 50 | `Status` Char(20), 51 | `Shippent_Duration` Varchar(20) NOT NULL, 52 | `Payment_ID` Char(3) NOT NULL 53 | ) 54 | ; 55 | 56 | CREATE INDEX `IX_Relationship15` ON `Orders` (`Payment_ID`) 57 | ; 58 | 59 | ALTER TABLE `Orders` ADD PRIMARY KEY (`Order_ID`) 60 | ; 61 | 62 | -- Table Customer 63 | 64 | CREATE TABLE `Customer` 65 | ( 66 | `Customer_ID` Char(5) NOT NULL, 67 | `First_Name` Varchar(20) NOT NULL, 68 | `Last_Name` Varchar(20) NOT NULL, 69 | `Phone_Number` Int(10) NOT NULL, 70 | `Email_Address` Varchar(20) NOT NULL, 71 | `Customer_Type` Varchar(20) NOT NULL 72 | ) 73 | ; 74 | 75 | ALTER TABLE `Customer` ADD PRIMARY KEY (`Customer_ID`) 76 | ; 77 | 78 | -- Table Zip Code 79 | 80 | CREATE TABLE `Zip Code` 81 | ( 82 | `State` Varchar(20) NOT NULL, 83 | `Zipcode_ID` Char(5) NOT NULL, 84 | `City` Varchar(20) NOT NULL, 85 | `Address_ID` Char(2) NOT NULL 86 | ) 87 | ; 88 | 89 | CREATE INDEX `IX_Relationship6` ON `Zip Code` (`Address_ID`) 90 | ; 91 | 92 | ALTER TABLE `Zip Code` ADD PRIMARY KEY (`Zipcode_ID`) 93 | ; 94 | 95 | -- Table Reviews 96 | 97 | CREATE TABLE `Reviews` 98 | ( 99 | `Quality_Rating` Int(1) NOT NULL, 100 | `Defect%` Int(2) NOT NULL, 101 | `Review_ID` Varchar(4) NOT NULL, 102 | `Review_Date` Date 103 | ) 104 | ; 105 | 106 | ALTER TABLE `Reviews` ADD PRIMARY KEY (`Review_ID`) 107 | ; 108 | 109 | -- Table Product 110 | 111 | CREATE TABLE `Product` 112 | ( 113 | `Product_ID` Char(5) NOT NULL, 114 | `Product_Name` Varchar(20) NOT NULL, 115 | `Available_Number` Int(200), 116 | `Group_ID` Int(3) NOT NULL, 117 | `Supplier_ID` Char(4) NOT NULL, 118 | `Review_ID` Varchar(4) 119 | ) 120 | ; 121 | 122 | CREATE INDEX `IX_Relationship1` ON `Product` (`Group_ID`) 123 | ; 124 | 125 | CREATE INDEX `IX_Relationship2` ON `Product` (`Supplier_ID`) 126 | ; 127 | 128 | CREATE INDEX `IX_Relationship3` ON `Product` (`Review_ID`) 129 | ; 130 | 131 | ALTER TABLE `Product` ADD PRIMARY KEY (`Product_ID`) 132 | ; 133 | 134 | -- Table Supplier 135 | 136 | CREATE TABLE `Supplier` 137 | ( 138 | `Supplier_ID` Char(4) NOT NULL, 139 | `Supplier_Name` Varchar(20) NOT NULL, 140 | `Supply_Quantity` Varchar(2000) NOT NULL 141 | ) 142 | ; 143 | 144 | ALTER TABLE `Supplier` ADD PRIMARY KEY (`Supplier_ID`) 145 | ; 146 | 147 | -- Table Payment 148 | 149 | CREATE TABLE `Payment` 150 | ( 151 | `Payment_ID` Char(3) NOT NULL, 152 | `Payment_Mode` Varchar(20) NOT NULL, 153 | `Card_Type` Varchar(20) NOT NULL, 154 | `Card_Number` Int(12) NOT NULL, 155 | `CVV` Int(11) NOT NULL, 156 | `Name_On_Card` Varchar(20) NOT NULL, 157 | `Customer_ID` Char(5) NOT NULL, 158 | `Visit_Number` Int NOT NULL 159 | ) 160 | ; 161 | 162 | CREATE INDEX `IX_Relationship11` ON `Payment` (`Customer_ID`) 163 | ; 164 | 165 | ALTER TABLE `Payment` ADD PRIMARY KEY (`Payment_ID`) 166 | ; 167 | 168 | -- Table Employees 169 | 170 | CREATE TABLE `Employees` 171 | ( 172 | `Employee_ID` Char(3) NOT NULL, 173 | `Employee_Name` Varchar(20) NOT NULL, 174 | `SSN` Int(9) NOT NULL, 175 | `Designation` Varchar(10) NOT NULL, 176 | `Employee_Type` Varchar(20) NOT NULL, 177 | `Salary` Varchar(20) NOT NULL, 178 | `Payment_ID` Char(3) NOT NULL 179 | ) 180 | ; 181 | 182 | CREATE INDEX `IX_Relationship8` ON `Employees` (`Payment_ID`) 183 | ; 184 | 185 | ALTER TABLE `Employees` ADD PRIMARY KEY (`Employee_ID`) 186 | ; 187 | 188 | -- Table Bill 189 | 190 | CREATE TABLE `Bill` 191 | ( 192 | `Billing_ID` Char(5) NOT NULL, 193 | `Billing_Date` Date NOT NULL, 194 | `Amount_Paid` Double NOT NULL, 195 | `Voucher_ID` Varchar(2), 196 | `Payment_ID` Char(3) NOT NULL, 197 | `Order_ID` Char(4) NOT NULL 198 | ) 199 | ; 200 | 201 | CREATE INDEX `IX_Relationship4` ON `Bill` (`Voucher_ID`) 202 | ; 203 | 204 | CREATE INDEX `IX_Relationship9` ON `Bill` (`Payment_ID`) 205 | ; 206 | 207 | CREATE INDEX `IX_Relationship16` ON `Bill` (`Order_ID`) 208 | ; 209 | 210 | ALTER TABLE `Bill` ADD PRIMARY KEY (`Billing_ID`) 211 | ; 212 | 213 | -- Table Voucher 214 | 215 | CREATE TABLE `Voucher` 216 | ( 217 | `Voucher_ID` Varchar(2) NOT NULL, 218 | `Discount%` Int(2) NOT NULL 219 | ) 220 | ; 221 | 222 | ALTER TABLE `Voucher` ADD PRIMARY KEY (`Voucher_ID`) 223 | ; 224 | 225 | -- Table Address 226 | 227 | CREATE TABLE `Address` 228 | ( 229 | `Address_ID` Char(2) NOT NULL, 230 | `Apartment_Number` Int NOT NULL, 231 | `Street` Varchar(20) NOT NULL, 232 | `Apartment_Name` Varchar(20) NOT NULL, 233 | `Customer_ID` Char(5) NOT NULL 234 | ) 235 | ; 236 | 237 | CREATE INDEX `IX_Relationship5` ON `Address` (`Customer_ID`) 238 | ; 239 | 240 | ALTER TABLE `Address` ADD PRIMARY KEY (`Address_ID`) 241 | ; 242 | 243 | -- Table Product Group 244 | 245 | CREATE TABLE `Product Group` 246 | ( 247 | `Group_ID` Int(3) NOT NULL, 248 | `Group_Name` Varchar(20) NOT NULL 249 | ) 250 | ; 251 | 252 | ALTER TABLE `Product Group` ADD PRIMARY KEY (`Group_ID`) 253 | ; 254 | 255 | -- Table Order Product 256 | 257 | CREATE TABLE `Order Product` 258 | ( 259 | `Quantity` Int(200), 260 | `Product_ID` Char(5) NOT NULL, 261 | `Order_ID` Char(4) NOT NULL 262 | ) 263 | ; 264 | 265 | CREATE INDEX `IX_Relationship12` ON `Order Product` (`Product_ID`) 266 | ; 267 | 268 | CREATE INDEX `IX_Relationship13` ON `Order Product` (`Order_ID`) 269 | ; 270 | 271 | ALTER TABLE `Order Product` ADD PRIMARY KEY (`Product_ID`,`Order_ID`) 272 | ; 273 | 274 | -- Table Product Details 275 | 276 | CREATE TABLE `Product Details` 277 | ( 278 | `Product_ID` Char(5) NOT NULL, 279 | `Weight` Varchar(20), 280 | `Width` Double(2,2), 281 | `Height` Double(2,2), 282 | `Colour` Varchar(20) 283 | ) 284 | ; 285 | 286 | ALTER TABLE `Product Details` ADD PRIMARY KEY (`Product_ID`) 287 | ; 288 | 289 | -- Table Customer Category 290 | 291 | CREATE TABLE `Customer Category` 292 | ( 293 | `Customer_Category` Varchar(20) NOT NULL, 294 | `Customer_ID` Char(5) NOT NULL 295 | ) 296 | ; 297 | 298 | ALTER TABLE `Customer Category` ADD PRIMARY KEY (`Customer_ID`) 299 | ; 300 | 301 | -- Create relationships section ------------------------------------------------- 302 | 303 | ALTER TABLE `Product` ADD CONSTRAINT `belongs to` FOREIGN KEY (`Group_ID`) REFERENCES `Product Group` (`Group_ID`) ON DELETE RESTRICT ON UPDATE RESTRICT 304 | ; 305 | 306 | ALTER TABLE `Product` ADD CONSTRAINT `supplies` FOREIGN KEY (`Supplier_ID`) REFERENCES `Supplier` (`Supplier_ID`) ON DELETE RESTRICT ON UPDATE RESTRICT 307 | ; 308 | 309 | ALTER TABLE `Product` ADD CONSTRAINT `are given` FOREIGN KEY (`Review_ID`) REFERENCES `Reviews` (`Review_ID`) ON DELETE RESTRICT ON UPDATE RESTRICT 310 | ; 311 | 312 | ALTER TABLE `Bill` ADD CONSTRAINT `is included` FOREIGN KEY (`Voucher_ID`) REFERENCES `Voucher` (`Voucher_ID`) ON DELETE RESTRICT ON UPDATE RESTRICT 313 | ; 314 | 315 | ALTER TABLE `Address` ADD CONSTRAINT `will have` FOREIGN KEY (`Customer_ID`) REFERENCES `Customer` (`Customer_ID`) ON DELETE RESTRICT ON UPDATE RESTRICT 316 | ; 317 | 318 | ALTER TABLE `Zip Code` ADD CONSTRAINT `will zip` FOREIGN KEY (`Address_ID`) REFERENCES `Address` (`Address_ID`) ON DELETE RESTRICT ON UPDATE RESTRICT 319 | ; 320 | 321 | ALTER TABLE `Employees` ADD CONSTRAINT `monitors` FOREIGN KEY (`Payment_ID`) REFERENCES `Payment` (`Payment_ID`) ON DELETE RESTRICT ON UPDATE RESTRICT 322 | ; 323 | 324 | ALTER TABLE `Bill` ADD CONSTRAINT `Generates` FOREIGN KEY (`Payment_ID`) REFERENCES `Payment` (`Payment_ID`) ON DELETE RESTRICT ON UPDATE RESTRICT 325 | ; 326 | 327 | ALTER TABLE `Payment` ADD CONSTRAINT `makes` FOREIGN KEY (`Customer_ID`) REFERENCES `Customer` (`Customer_ID`) ON DELETE RESTRICT ON UPDATE RESTRICT 328 | ; 329 | 330 | ALTER TABLE `Order Product` ADD CONSTRAINT `product order relation` FOREIGN KEY (`Product_ID`) REFERENCES `Product` (`Product_ID`) ON DELETE RESTRICT ON UPDATE RESTRICT 331 | ; 332 | 333 | ALTER TABLE `Order Product` ADD CONSTRAINT `contains` FOREIGN KEY (`Order_ID`) REFERENCES `Orders` (`Order_ID`) ON DELETE RESTRICT ON UPDATE RESTRICT 334 | ; 335 | 336 | ALTER TABLE `Orders` ADD CONSTRAINT `Orders` FOREIGN KEY (`Payment_ID`) REFERENCES `Payment` (`Payment_ID`) ON DELETE RESTRICT ON UPDATE RESTRICT 337 | ; 338 | 339 | ALTER TABLE `Bill` ADD CONSTRAINT `is billed` FOREIGN KEY (`Order_ID`) REFERENCES `Orders` (`Order_ID`) ON DELETE RESTRICT ON UPDATE RESTRICT 340 | ; 341 | 342 | ALTER TABLE `Product Details` ADD CONSTRAINT `has details` FOREIGN KEY (`Product_ID`) REFERENCES `Product` (`Product_ID`) ON DELETE RESTRICT ON UPDATE RESTRICT 343 | ; 344 | 345 | ALTER TABLE `Customer Category` ADD CONSTRAINT `belong` FOREIGN KEY (`Customer_ID`) REFERENCES `Customer` (`Customer_ID`) ON DELETE RESTRICT ON UPDATE RESTRICT 346 | ; 347 | 348 | --------------------------------------------------------------------------------