# Transform the e r diagram of figure 9 21 into a set of 3nf relations

Image by Samuel Mann A relational database, as we all know from the previous articlestores relations between integers, strings and other simple types in a very plain way: This model is extremely flexible, since other relations can be easily derived from existing ones using mathematical formulae, and the relational database takes care of that. However, database should reflect the real world in some way to be really of use. Since the relational databases store relations between mathematical abstractions and not real world things, we should make some kind of a mapping of ones to the others.

What is Data Modeling?

## Convert to Third Normal Form (3NF)

Data modeling is the act of exploring data-oriented structures. Like other modeling artifacts data models can be used for a variety of purposes, from high-level conceptual models to physical data models.

Common Data Modeling Notations. Figure 4 presents a summary of the syntax of four common data modeling Although I provide a brief description of each notation in Table 1 I highly suggest David Hay’s paper A Comparison of Data Modeling Techniques as he goes into greater detail than I do Figure 8. A normalized schema in 3NF (UML Notation). Systems Analysis and Design in a Changing World, Fourth Edition 12 Conversion of 2NF Table into 3NF Tables ZipCode determines the value for State, and ZipCode is not the key to the RMO Class Diagram (Figure ) 12 Systems Analysis and Design in a Changing World. Transform the E-R diagram of Figure into a set of 3NF relations. Make up a primary key and one or more monkeys for each entity. Transform the E-R diagram of Figure into a set of 3NF relations.

From the point of view of an object-oriented developer data modeling is conceptually similar to class modeling. With data modeling you identify entity types whereas with class modeling you identify classes.

Data attributes are assigned to entity types just as you would assign attributes and operations to classes. There are associations between entities, similar to the associations between classes — relationships, inheritance, composition, and aggregation are all applicable concepts in data modeling.

Traditional data modeling is different from class modeling because it focuses solely on data — class models allow you to explore both the behavior and data aspects of your domain, with a data model you can only explore data issues.

However, some people will model database methods stored procedures, stored functions, and triggers when they are physical data modeling. It depends on the situation of course, but I personally think that this is a good idea and promote the concept in my UML data modeling profile more on this later.

In fact, my experience is that CRC cards are superior to ORM diagrams because it is very easy to get project stakeholders actively involved in the creation of the model. Instead of a traditional, analyst -led drawing session you can instead facilitate stakeholders through the creation of CRC cards.

Although methodology issues are covered laterwe need to discuss how data models can be used in practice to better understand them. You are likely to see three basic styles of data model: These models, sometimes called domain models, are typically used to explore domain concepts with project stakeholders.

On Agile teams high-level conceptual models are often created as part of your initial requirements envisioning efforts as they are used to explore the high-level static business structures and concepts. Logical data models LDMs.

• Explore the Role of Normal Forms in Dimensional Modeling
• We see the following difference, in simple terms:
• ER/Studio Data Architect | Model and Optimize Enterprise Data
• Introduction

LDMs are used to explore the domain concepts, and their relationships, of your problem domain. This could be done for the scope of a single project or for your entire enterprise. LDMs depict the logical entity types, typically referred to simply as entity types, the data attributes describing those entities, and the relationships between the entities.

LDMs are rarely used on Agile projects although often are on traditional projects where they rarely seem to add much value in practice. Physical data models PDMs. PDMs are used to design the internal schema of a database, depicting the data tables, the data columns of those tables, and the relationships between the tables.

## Assume that at pine valley furniture products are composed, Other Engineering

Although LDMs and PDMs sound very similar, and they in fact are, the level of detail that they model can be significantly different. This is because the goals for each diagram is different — you can use an LDM to explore domain concepts with your stakeholders and the PDM to define your database design.

Figure 1 presents a simple LDM and Figure 2 a simple PDM, both modeling the concept of customers and addresses as well as the relationship between them. Both diagrams apply the Barker notationsummarized below.

Notice how the PDM shows greater detail, including an associative table required to implement the association as well as the keys needed to maintain the relationships. More on these concepts later. A PDM should also indicate the data types for the columns, such as integer and char 5.

A simple logical data model.5. Starting with the dependency diagram drawn for Problem 4, create a set of dependency diagrams that meet 3NF requirements. Rename attributes to meet the naming conventions, and create new entities and attributes as necessary.

The dependency diagrams in Figure P&9 reflect the notion that one employee manages each building. relation into separate relations, called normalized ones.

Figure 1 [9] illustrates the or ER, diagram and the product of this design phase is a conceptual schema. Transform E-R and EER diagrams to relations!

TRANSFORMING EER DIAGRAMS INTO RELATIONS (CONT.) Mapping Weak Entities 21 Figure Example of mapping a 1:M relationship a) Relationship between customers and orders Note the mandatory one b) Mapping the relationship.