PT 1: You have been asked to begin the database design for a Wedding Planner com

PT 1:
You have been asked to begin the database design for a Wedding Planner company. Convert the following ERD into a dependency diagram that is in at least 3NF.
App_Num:System-generated number
Planner_ID:Indentification number of the wedding planner
App_Date: The date of the appointment                                                                          Planner_FirstName: Wedding Planner’s first name.
App_Time: The time of the appointment.                                                                        Planner_LastName: Wedding Planner’s last name.
App_CustomerID: The ID number of the customer who made the appointment.            Planner_Phone: The planner’s phone number.
App_Name: The name of the customer.
App_Phone: The phone number of the customer.
App_Street: The customer’s street address.
App_City: The city the customer lives in.
App_State: The state the customer lives in.
App_Zip: The zip code for the customer’s address.
App_Status: The status of the appointment (active, closed, cancelled)
PT 2:
You are to begin the relational database design process for an invoicing system for a company that sells home improvement equipment. Use the table below to answer the questions listed below the table:
1) Write the relational schema, draw its dependency diagram, and identify all dependencies, including all partial and transitive dependencies.  Assum that an invoice number references more than one product (Hint: This table uses a composite primary key.). Also assume that the table will never contain repeating groups. Clearly label your drawing.
2)  Now, remove all partial dependencies, write the relational schema, and draw the new dependency diagrams. Identify the normal fomrs for each table structure you created.
Note: You can assume that any particular product is provided by one vendor; however, a vendor may provide many products, Thus, you can assume that the following dependency exists:
PROD_NUM –> PROD_LABEL, PROD_PRICE, VEND_CODE, VEND_NAME
You should produce three dependency diagrams.

***READ INSTRUCTIONS, serious bids only*** For my database class we are using my

***READ INSTRUCTIONS, serious bids only***
For my database class we are using mySQL or MySQLite for the backend and HTML/CSS, Python, PHP, or others for the front end.
The art gallery FF.doc is the proposal for what we want from the project
Project instructions are whats required from the project
Resized jpg is the database outline I created to give guidance
I don’t think it needs to be the most complex thing but it needs to get the job done

You have been asked to begin the database design for a Wedding Planner company.

You have been asked to begin the database design for a Wedding Planner company. Convert the following ERD into a dependency diagram that is in at least 3NF.
App_Num: System-generated number                                                 
Planner_ID: Identification number of the wedding planner
App_Date: The date of the appointment                                                                          Planner_FirstName: Wedding Planner’s first name.
App_Time: The time of the appointment.                                                                        Planner_LastName: Wedding Planner’s last name.
App_CustomerID: The ID number of the customer who made the appointment.            Planner_Phone: The planner’s phone number.
App_Name: The name of the customer.
App_Phone: The phone number of the customer.
App_Street: The customer’s street address.
App_City: The city the customer lives in.
App_State: The state the customer lives in.
App_Zip: The zip code for the customer’s address.
App_Status: The status of the appointment (active, closed, cancelled)

You are to begin the relational database design process for an invoicing system

You are to begin the relational database design process for an invoicing system for a company that sells home improvement equipment. Use the table below to answer the questions listed below the table:
1) Write the relational schema, draw its dependency diagram, and identify all dependencies, including all partial and transitive dependencies.  Assum that an invoice number references more than one product (Hint: This table uses a composite primary key.). Also assume that the table will never contain repeating groups. Clearly label your drawing.
2)  Now, remove all partial dependencies, write the relational schema, and draw the new dependency diagrams. Identify the normal fomrs for each table structure you created.
Note: You can assume that any particular product is provided by one vendor; however, a vendor may provide many products, Thus, you can assume that the following dependency exists:
PROD_NUM –> PROD_LABEL, PROD_PRICE, VEND_CODE, VEND_NAME
You should produce three dependency diagrams.

See the attached PDF or ONENOTE for instructions. START THIS ASSIGNMENT AS SOON

See the attached PDF or ONENOTE for instructions.
START THIS ASSIGNMENT AS SOON AS POSSILE AFTER COMPLETING THE PRIOR WORK!!!  (I know it is due in a couple of days but START NOW). Most will need to submit MULTIPLE ATTEMPTS. You should submit early if you would like faster feedback.
This exercise will be used as part of the Project: Build a Knowledge Engine. It is not optional. Several attempts based on my feedback will be necessary to complete it throughout the course.
WARNING:  You will not be able to finish the projects in this course correctly if this document is not almost perfect! Below is a general path to a successful database creation project. Think of it as a snapshot of the rest of the course.
Produce a basic ERD (Entity Relationship Diagram)
Produce a NOMALIZATION Document
Use the NORMALIZATION Document as a guide to ffinalize the ERD
Use the ERD as a guide to create a DATA DEFINITION Document (using DDL – Data Definition Language)
Use the DATA DEFINITION Doc as a guide to produce  ETL-SQL STATEMENT Document (Data Markup Language – DML) – DML is used to populate (fill) your tables with data, query your data, and update your data.
Use 1-5 to Build the Knowledge Engine (Database).

https://study.com/academy/lesson/database-programming-assignment-creating-manipu

https://study.com/academy/lesson/database-programming-assignment-creating-manipulating-a-database.html
About this Assignment
This is a Database Programming course. This course covers advanced topics in databases. It starts by reviewing basic knowledge on databases and ends with advanced database concepts like security.
In this project, you will use the knowledge you acquired throughout the course to build a simple database and query it to extract information from it. You will create tables and relationships among them, in addition to the necessary keys and indexes. The next step will be to populate the database with suitable data. Populating the tables with sufficient and appropriate example data is an important step in testing and validating your design. When your database is ready, you will write SQL queries to retrieve information.
Upon completion of this project, you will be able to:
Write SQL queries to create tables
Write SQL queries to create relationships among tables
Identify indexes and create them in a database
Write queries to extract important information from a database
Prompt
In this project you will build a database for a public library. This database is aimed to collect and analyze information about the clients’ reading interests. The project concentrates only on books and the clients’ interests in books. The analyses that will result from this project will be used by the library’s management to decide on the future purchasing policy.
A. Write the SQL statements in order to create the tables for the database. Use the Entity Relationship Diagram (ERD) of the database shown in Figure 1. For simplicity, we are assuming in this project that a book cannot be written by more than one author. You need to create the tables as well as the required constraints, including the keys (primary and foreign), and the relationships between tables.
Figure 1: ERD for Library Database ERD diagram
B. Populate your database with the sample set of data given to you in the tables below the assignment prompts.
C. Write the following queries to retrieve the information detailed below.
Display all contents of the Clients table
First names, last names, ages and occupations of all clients
First and last names of clients that borrowed books in March 2018
First and last names of the top 5 authors clients borrowed in 2017
Least 5 author nationalities clients borrowed during the years 2015-2017
The book that was most borrowed during the years 2015-2017
Top borrowed genres for client born in years 1970-1980
Top 5 occupations that borrowed the most in 2016
Average number of borrowed books by job title
Create a VIEW and display the titles that were borrowed by at least 20% of clients
The top month of borrows in 2017
Average number of borrows by age
The oldest and the youngest clients of the library
First and last names of authors that wrote books in more than one genre
As you work on these queries, create indexes that will increase your queries’ performance.
You must include comments in your code that address the purpose of your query and explains each step. Save your queries and results in a plain-text file that you will submit as your assignment.
Author table:
AuthorId     AuthorFirstName     AuthorLastName     AuthorNationality
1     Sofia     Smith     Canada
2     Maria     Brown     Brazil
3     Elena     Martin     Mexico
4     Zoe     Roy     France
5     Sebastian     Lavoie     Canada
6     Dylan     Garcia     Spain
7     Ian     Cruz     Mexico
8     Lucas     Smith     USA
9     Fabian     Wilson     USA
10     Liam     Taylor     Canada
11     William     Thomas     Great Britain
12     Logan     Moore     Canada
13     Oliver     Martin     France
14     Alysha     Thompson     Canada
15     Isabelle     Lee     Canada
16     Emily     Clark     USA
17     John     Young     China
18     David     Wright     Canada
19     Thomas     Scott     Canada
20     Helena     Adams     Canada
21     Sofia     Carter     USA
22     Liam     Parker     Canada
23     Emily     Murphy     USA
Book table:
BookID     BookTitle     BookAuthor     Genre
1     Build your database system     1     Science
2     The red wall     2     Fiction
3     The perfect match     3     Fiction
4     Digital Logic     4     Science
5     How to be a great lawyer     5     Law
6     Manage successful negotiations     6     Society
7     Pollution today     7     Science
8     A gray park     2     Fiction
9     How to be rich in one year     8     Humor
10     Their bright fate     9     Fiction
11     Black lines     10     Fiction
12     History of theater     11     Literature
13     Electrical transformers     12     Science
14     Build your big data system     1     Science
15     Right and left     13     Children
16     Programming using Python     1     Science
17     Computer networks     14     Science
18     Performance evaluation     15     Science
19     Daily exercise     16     Well being
20     The silver uniform     17     Fiction
21     Industrial revolution     18     History
22     Green nature     19     Well being
23     Perfect football     20     Well being
24     The chocolate love     21     Humor
25     Director and leader     22     Society
26     Play football every week     20     well being
27     Maya the bee     13     Children
28     Perfect rugby     20     Well being
29     The end     23     Fiction
30     Computer security     1     Science
31     Participate     22     Society
32     Positive figures     3     Fiction
Client table:
ClientId     ClientFirstName     ClientLastName     ClientDoB     Occupation
1     Kaiden     Hill     2006     Student
2     Alina     Morton     2010     Student
3     Fania     Brooks     1983     Food Scientist
4     Courtney     Jensen     2006     Student
5     Brittany     Hill     1983     Firefighter
6     Max     Rogers     2005     Student
7     Margaret     McCarthy     1981     School Psychologist
8     Julie     McCarthy     1973     Professor
9     Ken     McCarthy     1974     Securities Clerk
10     Britany     O’Quinn     1984     Violinist
11     Conner     Gardner     1998     Licensed Massage Therapist
12     Mya     Austin     1960     Parquet Floor Layer
13     Thierry     Rogers     2004     Student
14     Eloise     Rogers     1984     Computer Security Manager
15     Gerard     Jackson     1979     Oil Exploration Engineer
16     Randy     Day     1986     Aircraft Electrician
17     Jodie     Page     1990     Manufacturing Director
18     Coral     Rice     1996     Window Washer
19     Ayman     Austin     2002     Student
20     Jaxson     Austin     1999     Repair Worker
21     Joel     Austin     1973     Police Officer
22     Alina     Austin     2010     Student
23     Elin     Austin     1962     Payroll Clerk
24     Ophelia     Wolf     2004     Student
25     Eliot     McGuire     1967     Dentist
26     Peter     McKinney     1968     Professor
27     Annabella     Henry     1974     Nurse
28     Anastasia     Baker     2001     Student
29     Tyler     Baker     1984     Police Officer
30     Lilian     Ross     1983     Insurance Agent
31     Thierry     Arnold     1975     Bus Driver
32     Angelina     Rowe     1979     Firefighter
33     Marcia     Rowe     1974     Health Educator
34     Martin     Rowe     1976     Ship Engineer
35     Adeline     Rowe     2005     Student
36     Colette     Rowe     1963     Professor
37     Diane     Clark     1975     Payroll Clerk
38     Caroline     Clark     1960     Dentist
39     Dalton     Clayton     1982     Police Officer
40     Steve     Clayton     1990     Bus Driver
41     Melanie     Clayton     1987     Computer Engineer
42     Alana     Wilson     2007     Student
43     Carson     Byrne     1995     Food Scientist
44     Conrad     Byrne     2007     Student
45     Ryan     Porter     2008     Student
46     Elin     Porter     1978     Computer Programmer
47     Tyler     Harvey     2007     Student
48     Arya     Harvey     2008     Student
49     Serena     Harvey     1978     School Teacher
50     Lilly     Franklin     1976     Doctor
51     Mai     Franklin     1994     Dentist
52     John     Franklin     1999     Firefighter
53     Judy     Franklin     1995     Firefighter
54     Katy     Lloyd     1992     School Teacher
55     Tamara     Allen     1963     Ship Engineer
56     Maxim     Lyons     1985     Police Officer
57     Allan     Lyons     1983     Computer Engineer
58     Marc     Harris     1980     School Teacher
59     Elin     Young     2009     Student
60     Diana     Young     2008     Student
61     Diane     Young     2006     Student
62     Alana     Bird     2003     Student
63     Anna     Becker     1979     Security Agent
64     Katie     Grant     1977     Manager
65     Joan     Grant     2010     Student
66     Bryan     Bell     2001     Student
67     Belle     Miller     1970     Professor
68     Peggy     Stevens     1990     Bus Driver
69     Steve     Williamson     1975     HR Clerk
70     Tyler     Williamson     1999     Doctor
71     Izabelle     Williamson     1990     Systems Analyst
72     Annabel     Williamson     1960     Cashier
73     Mohamed     Waters     1966     Insurance Agent
74     Marion     Newman     1970     Computer Programmer
75     Ada     Williams     1986     Computer Programmer
76     Sean     Scott     1983     Bus Driver
77     Farrah     Scott     1974     Ship Engineer
78     Christine     Lambert     1973     School Teacher
79     Alysha     Lambert     2007     Student
80     Maia     Grant     1984     School Teacher
Borrower table:
BorrowId     ClientId     BookId     BorrowDate
1     35     17     20/07/2016
2     1     3     19/04/2017
3     42     8     03/10/2016
4     62     16     05/04/2016
5     53     13     17/01/2017
6     33     15     26/11/2015
7     40     14     21/01/2015
8     64     2     10/09/2017
9     56     30     02/08/2017
10     23     2     28/06/2018
11     46     19     18/11/2015
12     61     20     24/11/2015
13     58     7     17/06/2017
14     46     16     12/02/2017
15     80     21     18/03/2018
16     51     23     01/09/2015
17     49     18     28/07/2015
18     43     18     04/11/2015
19     30     2     10/08/2018
20     48     24     13/05/2015
21     71     5     05/09/2016
22     35     3     03/07/2016
23     57     1     17/03/2015
24     23     25     16/08/2017
25     20     12     24/07/2018
26     25     7     31/01/2015
27     72     29     10/04/2016
28     74     20     31/07/2017
29     53     14     20/02/2016
30     32     10     24/07/2017
31     12     15     25/04/2018
32     77     13     09/06/2017
33     30     4     24/10/2017
34     37     24     14/01/2016
35     27     26     05/06/2017
36     1     16     06/05/2018
37     21     9     19/03/2016
38     69     28     29/03/2017
39     17     19     14/03/2017
40     8     9     22/04/2016
41     63     18     25/01/2015
42     65     20     10/10/2016
43     51     19     28/07/2015
44     23     12     25/01/2017
45     17     4     18/04/2017
46     68     5     06/09/2016
47     46     13     30/09/2017
48     15     13     05/07/2017
49     11     19     14/12/2017
50     78     15     26/01/2017
51     47     9     03/03/2015
52     68     7     26/05/2016
53     37     26     06/02/2017
54     48     27     30/12/2015
55     9     21     21/10/2017
56     29     8     01/04/2018
57     64     18     29/08/2017
58     61     26     21/02/2018
59     39     28     26/07/2016
60     73     18     22/08/2018
61     11     13     17/01/2018
62     45     6     20/07/2016
63     33     13     18/03/2018
64     10     17     06/06/2016
65     28     18     17/02/2017
66     51     3     09/12/2016
67     29     2     18/09/2015
68     28     30     14/09/2017
69     74     20     12/12/2015
70     15     22     14/01/2015
71     57     8     20/08/2017
72     2     5     18/01/2015
73     74     12     14/04/2018
74     51     10     25/02/2016
75     25     17     24/02/2015
76     45     21     10/02/2017
77     27     25     03/08/2016
78     32     28     15/06/2016
79     71     21     21/05/2017
80     75     26     03/05/2016
81     56     32     23/12/2015
82     26     32     16/05/2015
83     66     32     30/05/2015
84     57     18     15/09/2017
85     40     15     02/09/2016
86     65     4     17/08/2017
87     54     7     19/12/2015
88     29     4     22/07/2017
89     44     9     31/12/2017
90     56     31     13/06/2015
91     17     4     01/04/2015
92     35     16     19/07/2018
93     22     18     22/06/2017
94     39     24     29/05/2015
95     63     14     20/01/2018
96     53     21     31/07/2016
97     40     9     10/07/2016
98     52     4     05/04/2017
99     27     20     04/09/2016
100     72     29     06/12/2015
101     49     16     19/12/2017
102     6     12     04/12/2016
103     74     31     27/07/2016
104     48     32     29/06/2016
105     69     2     27/12/2016
106     60     32     29/10/2017
107     45     22     12/06/2017
108     42     15     14/05/2017
109     79     8     13/10/2016
110     70     18     04/12/2016
111     34     8     06/03/2016
112     43     8     19/12/2015
113     42     32     20/04/2016
114     67     5     06/03/2017
115     80     25     23/06/2015
116     54     11     03/05/2017
117     34     28     30/08/2017
118     65     20     26/08/2017
119     61     19     05/01/2018
120     38     12     17/01/2018
121     51     4     13/05/2016
122     7     16     17/03/2016
123     46     16     25/11/2016
124     75     30     12/08/2018
125     72     32     12/03/2015
126     44     17     15/06/2015
127     68     15     21/02/2016
128     21     1     19/06/2016
129     14     25     10/10/2016
130     68     21     27/05/2016
131     35     20     19/03/2015
132     16     27     08/08/2016
133     79     31     07/03/2018
134     14     17     28/04/2018
135     29     28     11/03/2018
136     41     4     08/08/2018
137     42     3     23/02/2016
138     45     3     10/07/2017
139     36     16     19/07/2018
140     36     30     07/08/2015
141     54     32     14/03/2018
142     61     15     28/03/2017
143     1     13     17/05/2018
144     43     1     14/05/2015
145     37     14     30/07/2015
146     62     17     19/09/2015
147     50     22     02/12/2016
148     45     1     24/07/2016
149     32     17     10/03/2018
150     13     28     14/02/2016
151     15     9     11/08/2018
152     10     19     29/08/2018
153     66     3     27/11/2016
154     68     29     12/07/2017
155     21     14     27/06/2018
156     35     9     22/01/2016
157     17     24     25/08/2016
158     40     21     09/07/2015
159     1     24     28/03/2016
160     70     27     10/07/2015
161     80     26     24/04/2016
162     29     5     18/10/2015
163     76     12     25/04/2018
164     22     4     24/12/2016
165     2     2     26/10/2017
166     35     13     28/02/2016
167     40     8     02/10/2017
168     68     9     03/01/2016
169     32     5     13/11/2016
170     34     17     15/09/2016
171     34     16     13/04/2018
172     80     30     13/10/2016
173     20     32     17/11/2015
174     36     10     01/09/2017
175     78     12     27/06/2018
176     57     8     22/03/2016
177     75     11     27/06/2017
178     71     10     01/08/2015
179     48     22     29/09/2015
180     19     16     21/02/2016
181     79     30     20/08/2018
182     70     13     16/09/2016
183     30     6     10/02/2017
184     45     12     12/10/2017
185     30     27     23/11/2016
186     26     3     13/08/2016
187     66     6     14/01/2017
188     47     15     10/02/2016
189     53     30     08/08/2018
190     80     16     31/03/2016
191     70     13     03/02/2018
192     14     25     27/03/2016
193     46     22     13/01/2016
194     30     32     06/08/2015
195     60     14     27/11/2016
196     14     13     23/05/2018
197     71     15     22/06/2016
198     38     21     27/12/2015
199     69     30     29/04/2017
200     49     31     03/06/2018
201     28     28     29/05/2015
202     49     3     30/08/2016
203     75     1     29/10/2015
204     78     3     12/05/2017
205     43     18     25/03/2015
206     27     21     22/02/2016
207     64     22     03/04/2015
208     21     11     09/12/2017
209     66     29     20/12/2016
210     45     13     15/04/2017
211     48     30     31/01/2015
212     20     25     20/12/2017
213     41     20     29/01/2018
214     51     12     05/07/2015
215     5     1     12/04/2015
216     40     3     24/02/2018
217     79     4     27/06/2018
218     15     10     01/11/2016
219     42     22     28/12/2016
220     17     9     29/01/2018
221     38     13     09/05/2016
222     79     2     06/12/2017
223     74     3     07/12/2015
224     46     8     05/06/2016
225     78     22     11/08/2018
226     45     2     20/04/2015
227     72     31     11/11/2015
228     18     17     21/03/2015
229     29     3     13/08/2017
230     66     11     05/06/2018
231     36     16     28/04/2016
232     26     2     23/10/2016
233     32     1     31/10/2017
234     62     14     25/07/2017
235     12     4     08/07/2015
236     38     32     24/02/2015
237     29     16     28/07/2016
238     36     25     07/05/2017
239     76     7     13/06/2015
240     28     16     15/08/2016
241     60     13     26/08/2016
242     8     3     28/07/2017
243     25     1     30/07/2016
244     62     29     24/08/2018
245     51     8     01/09/2016
246     27     23     08/02/2015
247     69     12     25/06/2018
248     51     12     04/07/2015
249     7     4     01/05/2015
250     31     15     29/10/2017
251     14     23     15/01/2015
252     14     1     21/05/2018
253     39     25     26/12/2015
254     79     24     31/05/2016
255     40     15     18/03/2016
256     51     13     13/04/2018
257     61     1     11/02/2015
258     15     24     02/03/2018
259     10     22     21/01/2018
260     67     10     08/07/2017
261     79     11     11/12/2016
262     19     32     04/05/2016
263     35     11     01/08/2017
264     27     13     15/12/2017
265     30     22     22/12/2015
266     8     7     26/06/2015
267     70     9     20/03/2016
268     56     18     29/01/2016
269     13     19     06/03/2015
270     61     2     18/06/2016
271     47     13     18/09/2017
272     30     22     19/02/2016
273     18     22     31/12/2016
274     34     29     27/10/2017
275     32     21     03/06/2015
276     9     28     30/03/2016
277     62     24     23/03/2015
278     44     22     29/04/2017
279     27     5     25/03/2015
280     61     28     14/07/2017
281     5     13     04/12/2016
282     43     19     15/03/2018
283     34     19     05/06/2016
284     35     5     19/02/2018
285     13     12     23/09/2016
286     74     18     26/12/2016
287     70     31     15/08/2017
288     42     17     15/06/2016
289     51     24     30/07/2018
290     45     30     15/01/2015
291     70     17     07/10/2017
292     77     7     06/01/2017
293     74     25     25/09/2015
294     47     14     01/02/2018
295     10     2     18/04/2017
296     16     21     03/10/2016
297     48     5     17/09/2016
298     72     3     10/02/2017
299     26     23     01/03/2016
300     49     23     25/10/2016

You are running your own store. You want to keep track of your customers’ inform

You are running your own store. You want to keep track of your customers’ information, merchandise information, orders, bills, receipts, likings, and feedback, restock-ing your merchandise, etc. You are free to choose the name of your store and what you sell. Make it a old video game store if possible please.
Your store should be unique and is about something you like or is passionate about.
You will use MySQL to create your DB. However, you will create two interfaces: one through Java and the other through PHP to experience the differences between both types.
Project Report sections:
o (2 points) Title page (your name, project title, semester, course name and number, instructor name) and  Name of store
o (6 points) Project description. Also list the software, tools, programming languages, etc. used and version.
o (6 points) DB schema
o (6 points)  ER/EER model/diagrams
o(30 points)  Print screens of DB of MySQL ( show tables, relations, attributes, etc.) Your grade will depend on the amount of information you will show.
o ( 10 points) List of queries both as English sentences and in SQL
o (15 points) Print screens of empty and full interfaces/forms/output windows of your Java GUI ( Pictures of all the different components of your project, both empty and running when using Java )
o (15 points) Print screens of empty and full web page forms of your PHP pages (Pictures of all the different components of your project, both empty and running when using PHP)
o (5 points) Conclusion. Reflect on your experience completing this project as an individual. The good and the bad. The time spent. Anything new you learned on your own. Compare between using Java and PHP as interfaces.
o (15  points) copy of Java code
o (15  points) copy of PHP code
Please put this all together in a word document. Thank you. This mini project has a fair amount of freedom.