2. Conceptual modeling
Conceptual modeling is a creation ER-diagram. ER-diagram it is graphically representing the logical relationships of entities. It is easier to work because you can differentiate amongst our visual communication entities. At this stage, the design we show the relationship between entities.
There are several types of communication: 1. One-to-one; 2. One-to-many; 3. Many-to-many; Linking each entity his primary key to become foreign key to another entity. Further to be able to work with these linked tables.
Below is a ER-diagram of my database:
3. Logical modeling
At this stage we draw the design of any person in the tables to get the ratio of the logical data model. At this stage, we can conclude that approximately differentiate amongst us to our table and what type of information is stored for each attribute. At this stage, we present ER-diagram in 3NF and delete unnecessary information, which may in the future create anomalies. 1) Final ER-diagram (after working with many-to-many, etc.)
2) Derive relations for logical data model. Every entity of the ER-diagram should be described as follows.
Medications entity
field's content |
field's name |
type, length |
note |
Medications ID |
med_id |
C(20) |
PK, |
Name drug |
name_drug |
C(20) |
mandatory field |
Brief abstract |
brief_abstract |
C(20) |
mandatory field |
Manufacturer |
man_id |
C(20) |
FK to Manufacturer |
Storage |
storage |
C(20) |
mandatory field |
Category |
cat_id |
C(20) |
FK to Category |
Basket entity
field's content |
field's name |
type, length |
note |
Order ID |
ord_id |
C(20) |
FK to Order |
Medications ID |
med_id |
C(20) |
FK to Medications |
Date |
date |
D |
mandatory field |
Order entity
field's content |
field's name |
type, length |
note |
Order ID |
ord_id |
C(20) |
PK, |
Customer ID |
cust_id |
C(30) |
FK to Customer |
Date |
date |
D |
mandatory field |
Customer entity
field's content |
field's name |
type, length |
note |
Customer ID |
cust_id |
C(30) |
PK |
Name |
name |
C(30) |
mandatory field |
Date order |
date_order |
D |
mandatory field |
Phone number |
num 1 |
N(14) |
mandatory field |
Phone number |
num 2 |
N(14) |
mandatory field |
Order ID |
ord_id |
C(20) |
FK to Order |
Manufacturers entity
field's content |
field's name |
type, length |
note |
Medications ID |
med_id |
C(20) |
PK, |
Name |
name |
C(25) |
mandatory field |
City |
city |
C(20) |
mandatory field |
Suppliers entity
field's content |
field's name |
type, length |
note |
Medications ID |
med_id |
C(20) |
PK, |
Name |
name |
C(25) |
mandatory field |
City |
city |
C(20) |
mandatory field |
Employees entity
field's content |
field's name |
type, length |
note |
Employees ID |
emp_id |
C(20) |
PK, FK |
Last name |
l.name |
C(25) |
mandatory field |
First name |
f.name |
C(25) |
mandatory field |
Position |
position |
N(8) |
mandatory field |
Medications ID |
med_id |
C(20) |
FK to Medications |
Address_emp entity
field's content |
field's name |
type, length |
note |
Employees ID |
emp_id |
C(20) |
PK,FK |
Name |
name |
C(25) |
mandatory field |
Address |
address |
C(20) |
mandatory field |
Phone number |
num1 |
N(14) |
mandatory field |
Phone number |
num2 |
N(14) |
mandatory field |
C(30) |
mandatory field |
Ingredients entity
field's content |
field's name |
type, length |
note |
Ingredients ID |
ing_id |
C(20) |
PK, |
Name |
name |
C(25) |
mandatory field |
Ingredient in recipe entity
field's content |
field's name |
type, length |
note |
Ingredients ID |
ing_id |
C(20) |
PK, |
Recipe ID |
rec_id |
C(50) |
FK to Recipe |
Amount |
amount |
N(10) |
mandatory field |
Recipe entity
field's content |
field's name |
type, length |
note |
Recipe ID |
rec_id |
C(20) |
PK,FK |
Name |
name |
C(25) |
mandatory field |
period |
period |
C(20) |
mandatory field |
Customer ID |
cust_id |
C(20) |
FK to Customer |
Medications ID |
med_id |
C(20) |
FK to Medications |
Note: N – for numeric, C – character, D – date.
3. Normalization: validate relations using normalization.
In this database, my aim is to achieve first three forms of normalization and to get rid of redundant data and any anomalies. According to first form of normalization, in each cell I shall have only one single data. As you can see above, there are only single information in every cell. I have followed this rule and tried to save only single data in one cell.
Therefore, here is everything ok.
Second, transitevely depend every non - primary key not dependt on each other to the med_id , which is Primary key in this entity.
Third, transitevely depend to the med_id , which is Primery key every non - primary key not depend on each other fully depend to the med_id , which is Primary key in this entity.