Papa_EX19_AC_CH05_GRADER_CAP_AS.zip
Exp19_Access_Ch05_CapAssessment – Paterson Credit Union 1.1
Exp19 Access Ch05 CapAssessment Paterson Credit Union 1.1
Access Chapter 5 Capstone Assessment – Paterson Credit Union
Project Description:
You work as a database administrator at the Paterson Credit Union. You are modifying a database to add validation, lookup fields, and an input mask. You will also modify queries to take advantage of advanced functions and features.
Start Access. Open the file named Exp19_Access_Ch05_CapAssessment_Paterson_Credit_Union.accdb. Grader has automatically added your last name to the beginning of the filename.
You want to make sure that the customer account types are documented and stored correctly. To do this you will create a table that will list each account type.
Use Design view to create a new table. Add AccountType as the first field name, with data type Short Text and field size 10. Ensure AccountType is set as the primary key. Save the table and name it AccountTypes. Add three records: Platinum, Silver, and Gold. Save and close the table.
Now, you wish to ensure that, when customers are added to your database, the phone number and account type must be entered. To do this you will set the PhoneNumber and AccountType fields as required fields.
Open the Customers table in Design view. Set the PhoneNumber and AccountType fields to Required. Save and close the table.
Paterson Credit Union only offers loans with interest rates between 2.0% and 10.25%. To ensure that no loans are offered outside of those constraints you will add a validation rule that will not allow loans outside of that range to the InterestRate field in the Loans table.
Open the Loans table in Design view. Establish a validation rule for the InterestRate field that requires the value to be greater than or equal to 2.0 but less than or equal to 10.25. Create validation text for the InterestRate: Value must be between 2 and 10.25 (no period). Save the table and switch to Datasheet view. Change the InterestRate in the first record to 1.9. The validation text appears. Press ESC to restore the original value. Close the Loans table.
You’ve made the PhoneNumber field required in the Customers table, but now you want to ensure that phone numbers are entered in a specific format. To do this you will add an input mask to the PhoneNumber field in the Customers table.
Open the Customers table in Design view. Add a phone number input mask for the PhoneNumber field, storing the symbols with the data.
You would like to easily add the account type for each customer without typing anything on your keyboard. To do this you will turn the AccountType field into a Lookup Wizard using the AccountTypes table, that you recently created, as the source.
Change the Data Type of the AccountType field to Lookup Wizard. Use the AccountTypes table for the values in the lookup field, select the AccountType field from the table, accept the default sort, accept default column widths, and then accept the default name AccountType. Save the table. Switch to Datasheet view.
Change the account type to Platinum in the first record. Close the table.
For ease of use, you would like for users to be able to indicate the minimum loan amount on which they would like to pull loan information. You will do this by adding a parameter criterion to the LoanAmount field in the Customer Loans Parameter query.
Open the Customer Loans Parameter query in Design view. Add criteria for the Amount field. The user should be prompted to Enter Minimum Loan Amount (no period). The query should display all records that have a loan Amount that is greater than or equal to the value entered as the parameter. Run the query. Enter 250000 when prompted to Enter Minimum Loan Amount. You should have five results. Ensure that the query results display a total at the bottom of the Date column, and an average at the bottom of the Amount column. Save and close the query.
You have noticed that a few of your customers are missing address information. You would like to address this by creating a query that returns only the customers that are missing addresses so that you can update that information. You will complete this by adding a field that indicates whether an address is missing then adding criteria to that field so that only customers with missing addresses are returned.
Open the Missing Addresses query in Design view. Add a new column to determine if a customer does not have an address on file. If the customer’s Address is null, it should display Missing. If not, it should display nothing. Name the column AddressPresent. Add criteria of Missing to the column you just created, so only the customers missing an address display. Move the AddressPresent field so it appears between PhoneNumber and Address. Run the query. Ensure only customers with null Address fields display. Save and close the query.
For simplicity, you are now interested in rounding the interest rates for each loan to the nearest whole number. To do so, you will utilize the Round function in the Loans by Interest Rate query.
Open the Loans By Interest Rate query in Design view. Create a new column to round the InterestRate of each Loan to the nearest whole number. Name the field RoundedRate. Run the query and verify the RoundedRate column displays whole numbers. Save and close the query.
Seeing what the total and average payments month over month are is important to your operation. To display this information, you will use the DatePart function to extract the month from the PaymentDate field then ensure that the query is grouped by month.
Open the Payment By Month query in Design view. Change the first column so that instead of grouping by the payment date, you group by the month. Use the DatePart function to extract the month from the date. Name the column MonthNumber. Group by the MonthNumber field and display the Sum of the first Total field and the Average of the Average field. Run the query. The first line should read 2 (as the month, representing February), with a total of $5,246.51 as the total payments received and $1,311.63 as the average payment amount. Ensure that the query results display a total at the bottom of the Total column, and an average at the bottom of the Average column. Save and close the query.
Finally, you would like to classify the various loans as either high or low priority for the Credit Union. To do this you will add a column that determines whether the interest rate for a loan is greater than or equal to 7.9%, as that is what is considered high priority.
Open the Refinance Candidates query in Design view. This query displays all adjustable loans in the database. Create a new column to display High Priority for all loans that have an InterestRate of 7.9% or more, and Low Priority otherwise. Name the field Priority. Run the query. Notice customers with the highest interest rate values show a higher priority. Save and close the query.
Save the database. Close the database, and then exit Access. Submit the database as directed.
EX19_AC_CH05_GRADER_CAP_AS_Instructions x
Grader – Instructions Access 2019 Project
Exp19_Access_Ch05_CapAssessment – Paterson Credit Union 1.1
Project Description:
You work as a database administrator at the Paterson Credit Union. You are modifying a database to add validation, lookup fields, and an input mask. You will also modify queries to take advantage of advanced functions and features.
Steps to Perform:
Step
Instructions
Points Possible
1
Start Access. Open the file named
Exp19_Access_Ch05_CapAssessment_Paterson_Credit_Union.accdb. Grader has automatically added your last name to the beginning of the filename.
0
2
You want to make sure that the customer account types are documented and stored correctly. To do this you will create a table that will list each account type.
Use Design view to create a new table. Add
AccountType as the first field name, with data type Short Text and field size
10. Ensure AccountType is set as the primary key. Save the table and name it
AccountTypes. Add three records:
Platinum,
Silver, and
Gold. Save and close the table.
4
3
Now, you wish to ensure that, when customers are added to your database, the phone number and account type must be entered. To do this you will set the PhoneNumber and AccountType fields as required fields.
Open the Customers table in Design view. Set the PhoneNumber and AccountType fields to Required. Save and close the table.
6
4
Paterson Credit Union only offers loans with interest rates between 2.0% and 10.25%. To ensure that no loans are offered outside of those constraints you will add a validation rule that will not allow loans outside of that range to the InterestRate field in the Loans table.
Open the Loans table in Design view. Establish a validation rule for the InterestRate field that requires the value to be greater than or equal to
2.0 but less than or equal to
10.25. Create validation text for the InterestRate:
Value must be between 2 and 10.25 (no period). Save the table and switch to Datasheet view. Change the InterestRate in the first record to
1.9. The validation text appears. Press ESC to restore the original value. Close the Loans table.
8
5
You’ve made the PhoneNumber field required in the Customers table, but now you want to ensure that phone numbers are entered in a specific format. To do this you will add an input mask to the PhoneNumber field in the Customers table.
Open the Customers table in Design view. Add a phone number input mask for the PhoneNumber field, storing the symbols with the data.
16
6
You would like to easily add the account type for each customer without typing anything on your keyboard. To do this you will turn the AccountType field into a Lookup Wizard using the AccountTypes table, that you recently created, as the source.
Change the Data Type of the AccountType field to Lookup Wizard. Use the AccountTypes table for the values in the lookup field, select the AccountType field from the table, accept the default sort, accept default column widths, and then accept the default name
AccountType. Save the table. Switch to Datasheet view.
8
7
Change the account type to
Platinum in the first record. Close the table.
2
8
For ease of use, you would like for users to be able to indicate the minimum loan amount on which they would like to pull loan information. You will do this by adding a parameter criterion to the LoanAmount field in the Customer Loans Parameter query.
Open the Customer Loans Parameter query in Design view. Add criteria for the Amount field. The user should be prompted to
Enter Minimum Loan Amount (no period). The query should display all records that have a loan Amount that is greater than or equal to the value entered as the parameter. Run the query. Enter
250000 when prompted to Enter Minimum Loan Amount. You should have five results. Ensure that the query results display a total at the bottom of the Date column, and an average at the bottom of the Amount column. Save and close the query.
16
9
You have noticed that a few of your customers are missing address information. You would like to address this by creating a query that returns only the customers that are missing addresses so that you can update that information. You will complete this by adding a field that indicates whether an address is missing then adding criteria to that field so that only customers with missing addresses are returned.
Open the Missing Addresses query in Design view. Add a new column to determine if a customer does not have an address on file. If the customer’s Address is null, it should display
Missing. If not, it should display nothing. Name the column
AddressPresent. Add criteria of
Missing to the column you just created, so only the customers missing an address display. Move the AddressPresent field so it appears between PhoneNumber and Address. Run the query. Ensure only customers with null Address fields display. Save and close the query.
10
10
For simplicity, you are now interested in rounding the interest rates for each loan to the nearest whole number. To do so, you will utilize the Round function in the Loans by Interest Rate query.
Open the Loans By Interest Rate query in Design view. Create a new column to round the InterestRate of each Loan to the nearest whole number. Name the field
RoundedRate. Run the query and verify the RoundedRate column displays whole numbers. Save and close the query.
10
11
Seeing what the total and average payments month over month are is important to your operation. To display this information, you will use the DatePart function to extract the month from the PaymentDate field then ensure that the query is grouped by month.
Open the Payment By Month query in Design view. Change the first column so that instead of grouping by the payment date, you group by the month. Use the DatePart function to extract the month from the date. Name the column
MonthNumber. Group by the MonthNumber field and display the Sum of the first Total field and the Average of the Average field. Run the query. The first line should read 2 (as the month, representing February), with a total of $5,246.51 as the total payments received and $1,311.63 as the average payment amount. Ensure that the query results display a total at the bottom of the Total column, and an average at the bottom of the Average column. Save and close the query.
10
12
Finally, you would like to classify the various loans as either high or low priority for the Credit Union. To do this you will add a column that determines whether the interest rate for a loan is greater than or equal to 7.9%, as that is what is considered high priority.
Open the Refinance Candidates query in Design view. This query displays all adjustable loans in the database. Create a new column to display
High Priority for all loans that have an InterestRate of 7.9% or more, and
Low Priority otherwise. Name the field
Priority. Run the query. Notice customers with the highest interest rate values show a higher priority. Save and close the query.
10
13
Save the database. Close the database, and then exit Access. Submit the database as directed.
0
Total Points
100
Created On: 07/11/2019 1 Exp19_Access_Ch05_CapAssessment – Paterson Credit Union 1.1
Papa_Exp19_Access_Ch05_CapAssessment_Paterson_Credit_Union.accdb
CustomerID
FirstName
LastName
Address
City
State
ZipCode
PhoneNumber
AccountType
mSysRowId
1
Virginia
Stewart
7245 NW 8 Street
Minneapolis
MN
55346
6128941511
Gold
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
2
Gina
Mullins
5660 NW 175 Terrace
Baltimore
MD
21224
4107530345
Silver
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
3
Omar
Barton
10000 Sample Road
Coral Springs
FL
33073
3054445555
Platinum
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
4
Melissa
Lynch
7500 Reno Road
Houston
TX
77090
7134273104
Platinum
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
5
Aaron
Figueroa
3456 Main Highway
Denver
CO
80228
3035556666
Silver
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
6
Shannon
Abbott
2-2 Murray Street
Chapel Hill
NC
27515
9199427654
Gold
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
7
Morris
Cook
7075423411
Gold
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
8
Krista
Williams
9043745660
Gold
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
9
Jessie
Richards
5070 Battle Road
Decatur
GA
30034
3013456556
Silver
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
10
Jesus
Sutton
777 NW 67 Avenue
Fort Lee
NJ
07624
2016643211
Platinum
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
11
Roberta
Harmon
409 Cook Road
Stoneboro
Pa
16137
7245551212
Platinum
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
15
Joyce
Byrd
17 Snow Goose Place
Altenburg
MO
63732
9692598500
Gold
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
16
Arnold
Porter
1085 Alana Drive
Colorado City
AZ
86021
9509375705
Silver
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
17
Esther
Moreno
858 Toadstool Road
Mayfield
UT
84643
9595997109
Platinum
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
18
Alan
Adkins
3512243437
Gold
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
19
Perry
Sanchez
2028 Prentice Drive
Clifton
NJ
07012
4249352241
Silver
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
20
Nicholas
Fowler
2087 Ondola Lane
Dallas
SD
57529
8337024885
Platinum
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
21
Yvonne
Tucker
1674 Casper Street
Van Buren
AR
72956
9596058273
Gold
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
22
Nadine
Christensen
539 July Creek Street
Browntown
WI
53522
6006664583
Silver
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
23
Garry
Gross
8579824012
Platinum
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
24
Ruben
Rodgers
2334 Imperial Circle
Hollansburg
OH
45332
9987362069
Gold
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
25
Joel
Brady
954 Kidron Way
Star
TX
76880
8223268280
Silver
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
26
Courtney
Santos
1018 Eide Terrace
Hiram
MO
63947
9768057256
Platinum
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
27
Milton
Page
1197 Cyclone Terrace
Cloverdale
IN
46120
9504711359
Gold
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
28
Rufus
Gibbs
1403 Maytag Lane
Saint Regis
MT
59866
2246105693
Silver
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
29
Heather
Fuller
900 Midland Circle
Lexington
OK
73051
5552135251
Platinum
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
30
Charlie
Quinn
1513 Valarian Boulevard
Nashua
NH
03063
3002422114
Gold
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
31
Linda
Obrien
9768493226
Silver
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
32
George
Stevenson
126 Allison Terrace
Sanger
CA
93657
6006531035
Platinum
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
33
Johanna
Stephens
1351 Stonebridge Circle
Danforth
IL
60930
8304946646
Gold
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
34
Kate
Simmons
1708 Stemp Court
Crab Orchard
NE
68332
7115293270
Silver
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
35
Neil
Warren
1552 Sportsman Way
Washington
DC
20421
9596469432
Platinum
WVoBOJM5oy4q+u24n3kfsQOpUrsVEID/JGzlAuYjpgw=-~Az1hV5R4WpMamBW8M1W6SQ==
LoanID
Date
Amount
InterestRate
Term
Type
CustomerID
Adjustable
mSysRowId
1
2019-01-15
¤ 473,500.00
6.07
15
M
4
false
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
2
2019-01-23
¤ 36,500.00
7.07
5
c
4
true
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
3
2019-01-25
¤ 11,500.00
5.37
3
C
5
false
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
4
2019-01-31
¤ 13,500.00
9.63
10
O
4
true
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
5
2019-02-08
¤ 523,500.00
6.37
30
M
6
true
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
6
2019-02-12
¤ 12,000.00
7.63
5
O
7
true
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
7
2019-02-15
¤ 36,500.00
6.37
5
O
8
false
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
8
2019-02-20
¤ 248,500.00
8.93
30
M
8
false
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
9
2019-02-21
¤ 6,500.00
10.13
3
O
8
false
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
10
2019-02-28
¤ 198,500.00
6.87
15
M
1
false
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
11
2019-03-01
¤ 26,500.00
10.13
3
C
2
false
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
12
2019-03-01
¤ 21,500.00
9.63
5
O
5
true
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
13
2019-03-03
¤ 57,500.00
7.63
5
C
9
true
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
14
2019-03-10
¤ 127,500.00
8.63
15
m
10
false
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
15
2019-03-11
¤ 198,500.00
7.12
15
m
3
false
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
16
2019-03-21
¤ 148,500.00
7.63
15
M
1
false
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
17
2019-03-22
¤ 98,500.00
6.87
30
M
1
true
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
18
2019-03-31
¤ 16,500.00
6.37
3
o
3
true
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
19
2019-04-01
¤ 11,500.00
8.13
5
C
2
false
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
20
2019-04-15
¤ 26,500.00
8.63
4
c
3
false
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
21
2019-04-18
¤ 42,500.00
10.03
4
C
8
false
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
22
2019-04-22
¤ 348,500.00
7.63
15
m
10
true
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
23
2019-05-01
¤ 148,500.00
5.87
15
M
3
false
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
24
2019-05-03
¤ 348,500.00
8.33
30
M
4
true
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
25
2019-05-08
¤ 273,500.00
9.33
15
M
7
false
w/vvL+XHYp3S5s49hgkAKcuNv0psBEBdoNbr/gSfO9Y=-~LxL/flNAQgs+VtQYyoOqdw==
Type
LoanName
mSysRowId
C
Car
mhV/q5hW91tYcdh+wcy6SyAxNoqJqHKMnMnMLOQU9sQ=-~4L9g6hdLVDwcTkPHqk2uYg==
M
Mortgage
mhV/q5hW91tYcdh+wcy6SyAxNoqJqHKMnMnMLOQU9sQ=-~4L9g6hdLVDwcTkPHqk2uYg==
O
Personal
mhV/q5hW91tYcdh+wcy6SyAxNoqJqHKMnMnMLOQU9sQ=-~4L9g6hdLVDwcTkPHqk2uYg==
ID
mSysRowId
1
0XI/ucs8eH0C414G0owUnmc7ic3tYV26zFYvDzULrtI=-~LJFcRXT03PM7vLlsLe1VUQ==
PaymentID
LoanID
PaymentDate
AmountReceived
mSysRowId
1
1
2019-02-15
¤ 4,317.92
2
2
2019-02-15
¤ 621.35
3
3
2019-02-25
¤ 226.96
4
4
2019-02-28
¤ 80.28
5
5
2019-03-08
¤ 3,393.36
6
6
2019-03-12
¤ 135.40
7
1
2019-03-15
¤ 4,317.92
8
2
2019-03-15
¤ 621.35
9
7
2019-03-15
¤ 609.82
10
8
2019-03-20
¤ 2,050.69
11
9
2019-03-21
¤ 86.34
12
3
2019-03-25
¤ 226.96
13
10
2019-03-28
¤ 1,872.66
14
4
2019-03-31
¤ 80.28
15
11
2019-04-01
¤ 731.68
16
12
2019-04-01
¤ 345.04
17
5
2019-04-08
¤ 3,393.36
18
14
2019-04-10
¤ 1,195.31
19
15
2019-04-11
¤ 1,900.73
20
6
2019-04-12
¤ 135.40
21
1
2019-04-15
¤ 4,317.92
22
2
2019-04-15
¤ 621.35
23
7
2019-04-15
¤ 609.82
24
8
2019-04-20
¤ 2,050.69
25
9
2019-04-21
¤ 86.34
26
16
2019-04-21
¤ 1,315.52
27
17
2019-04-22
¤ 590.30
28
3
2019-04-25
¤ 226.96
29
10
2019-04-28
¤ 1,872.66
30
4
2019-04-30
¤ 80.28
31
18
2019-04-30
¤ 384.74
32
11
2019-05-01
¤ 731.68
33
12
2019-05-01
¤ 345.04
34
19
2019-05-01
¤ 127.76
35
5
2019-05-08
¤ 3,393.36
36
14
2019-05-10
¤ 1,195.31
37
15
2019-05-11
¤ 1,900.73
38
6
2019-05-12
¤ 135.40
39
1
2019-05-15
¤ 4,317.92
40
2
2019-05-15
¤ 621.35
41
7
2019-05-15
¤ 609.82
42
20
2019-05-15
¤ 541.21
43
21
2019-05-18
¤ 962.90
44
8
2019-05-20
¤ 2,050.69
45
9
2019-05-21
¤ 86.34
46
16
2019-05-21
¤ 1,315.52
47
17
2019-05-22
¤ 590.30
48
22
2019-05-22
¤ 3,319.54
49
3
2019-05-25
¤ 226.96
50
10
2019-05-28
¤ 1,872.66
51
4
2019-05-30
¤ 80.28
52
18
2019-05-30
¤ 384.74
53
11
2019-06-01
¤ 731.68
54
12
2019-06-01
¤ 345.04
55
19
2019-06-01
¤ 127.76
56
23
2019-06-01
¤ 1,190.79
57
24
2019-06-03
¤ 2,692.14
58
5
2019-06-08
¤ 3,393.36
59
25
2019-06-08
¤ 2,897.05
60
14
2019-06-10
¤ 1,195.31
61
15
2019-06-11
¤ 1,900.73
62
6
2019-06-12
¤ 135.40
63
1
2019-06-15
¤ 4,317.92
64
2
2019-06-15
¤ 621.35
65
7
2019-06-15
¤ 609.82
66
20
2019-06-15
¤ 541.21
67
21
2019-06-18
¤ 962.90
68
8
2019-06-20
¤ 2,050.69
69
9
2019-06-21
¤ 86.34
70
16
2019-06-21
¤ 1,315.52
71
17
2019-06-22
¤ 590.30
72
22
2019-06-22
¤ 3,319.54
73
3
2019-06-25
¤ 226.96
74
10
2019-06-28
¤ 1,872.66
75
4
2019-06-30
¤ 80.28
76
18
2019-06-30
¤ 384.74
SELECT LoanTypes.LoanName, Loans.Date, Loans.Amount, Loans.Term, Loans.Adjustable
FROM LoanTypes INNER JOIN Loans ON LoanTypes.Type = Loans.Type;
SELECT Loans.LoanID, Loans.Date, Loans.Amount, Loans.InterestRate, Loans.Term, Loans.Type, Loans.Adjustable
FROM Loans;
SELECT Customers.FirstName, Customers.LastName, Customers.PhoneNumber, Customers.Address, Customers.City, Customers.State, Customers.ZipCode
FROM Customers;
SELECT Payments.PaymentDate, Payments.AmountReceived AS Total, Payments.AmountReceived AS Average
FROM Payments;
SELECT Customers.FirstName, Customers.LastName, Customers.PhoneNumber, Loans.InterestRate, LoanTypes.LoanName, Loans.Adjustable
FROM Customers INNER JOIN (LoanTypes INNER JOIN Loans ON LoanTypes.Type = Loans.Type) ON Customers.CustomerID = Loans.CustomerID
WHERE (((Loans.Adjustable)=Yes))
ORDER BY Loans.InterestRate DESC;
Order an Essay Now & Get These Features For Free:
Turnitin Report
Formatting
Title Page
Citation
Outline
