The previous chapter focused on the flow of information and processes, while Chapter 8 of MSAD focused on data requirements. Data models are important because they can serve as the foundation for database design. And since data are often the most complex aspects of information systems, data modeling needs to be comprehensive and accurate. One interesting point I found was that “an information system design based on a data orientation, rather than a process or logic orientation, should have a longer useful life and should have common features for the same applications or domains in different organizations.”
ERDs, or entity relationship diagrams, are the most common form used for data modeling. Class diagrams are used for object-oriented analysis. You can go about it with either a top-down or bottom-up approach. Top-down comes from an intimate understanding of the nature of the business. Bottom-up comes from reviewing business documents and knowing what data are needed. An entity is a person, place, object, event, or concept about which the organization wishes to maintain data. An entity type (sometimes called an entity class) is a collection of entities that share common properties or characteristics. An entity instance is a single occurrence of an entity type. It’s important to have clear, descriptive names so everyone knows what is being referenced. Thus there are specific entity and attribute naming guidelines.
The display of the relationships are important in these data models. The three most common types are unary, binary and ternary. Unary is a recursive relationship. Binary is between instances of two entity types (most common). Ternary a relationship among three entity types. Diagrams can show mandatory or optional relationships and even subtypes and supertypes (hierarchy).
Industry-specific data models are common and packaged data models can reduce cost for an organization.
Elias Harake says
A key takeaway that I thought was interesting from this week’s Chapter 8 reading was how data can be better represented using entity-relationship models. I learned the guidelines for well-structured and efficient database files, and you will learn about logical and physical database design. The individual interface and database design steps usually happen simultaneously, as illustrated in the systems development life cycle (SDLC). However, structure the data in stable structures, called normalized tables, that are not likely to change over time and that have minimal redundancy. Most information systems today use relational database management systems, logical database design usually uses relational database models, which illustrate data in more simple tables with common columns to link related table information. Also, the implementation of a database is done during the next phase of the systems development life cycle.
Priyanka Ranu says
One of the ways an ERD can be enhanced during the logical design phase is through the process of normalization. Normalization is the process of removing redundancy in a table so that the table is easier to modify. It usually involves dividing an entity table into two or more tables and defining relationships between them. The objective of normalization is to isolate data so that any modifications of an attribute can be made in one table. Performing normalization during ERD development can improve the conceptual model and speed its implementation.
Priyanka Ranu says
I learned about entity relationship data model which is a detailed logical representation of the data for an organization or for a business case. Entity-relationship diagram is a graphical representation of an E-R model. There are three main constructs which are data entities, relationships, and their associated attributes. The goal is to capture as much of the meaning of the data as possible as more details about data is modeled, the better the system can be built and designed. The advantage of E-R model is that the data requirements are easily understandable as it has clearly defined entities and the relations between them.
Taylor Trench says
A main concept from this unit’s reading that stood out to me was the concept of E-R modeling. The entity-relationship data model is a logical representation of the various elements of an organization, such as data, entities, and associations. The entity-relationship diagram is a graphical representation of this model. The three main components within E-R modeling are data entities, relationships, and attributes. Entities are identified within an organization, and their relationships are defined. Entities are also given attributes, which are properties used to describe these entities. The concept of E-R modeling is so important in the analysis phase of systems development because it helps the systems analyst understand the data within a system, including how different types of data relate to one another. Understanding these relationships and entities helps the systems analyst determine the system requirements for the organization. Personally, I find this analysis method to be extremely useful, specifically the E-R diagram. This helps visualize the system extremely well, especially if the E-R diagram is done with a high level of detail.
Haozhe Lin says
I like this week’s main concept that is ER diagram. An ER diagram shows the relationship among entity sets. An entity set is a group of similar entities and these entities can have attributes. In terms of DBMS, an entity is a table or attribute of a table in the database, so by showing the relationship among tables and their attributes, ER diagram shows the complete logical structure of a database. Let’s have a look at a simple ER diagram to understand this concept. why use ER modeling when we can simply create the database and all of its objects without ER modeling? One of the challenges faced when designing a database is the fact that designers, developers, and end-users tend to view data and its usage differently. If this situation is left unchecked, we can end up producing a database system that does not meet the requirements of the users. Communication tools understood by all stakeholders(technical as well as non-technical users) are critical in producing database systems that meet the requirements of the users. ER models are examples of such tools.
Cami Chen says
The one of key points in chapter 8 that I want to talk about is how the data model is employed when structuring system data requirements. The business needs to meet serval requirements determination for data modeling:
-The data entities and the data descriptions should be relevant to the business objective.
-The ability to identify the primary key that distinguishes between the object of the same type.
-The ability to verify attributes and secondary keys to how the data should be selected and run the business.
-Understand the security controls and who through recognize the meaning of the data for the business, and how to use it appropriately.
-Determine cardinality and time dimensions of data that select appropriately the period of time in the data.
-Follow the integrity rules that minimum and maximum cardinality and time dimensions of data. Ensure that an event manages in the same way and with some or all the associated objects.
Once the system users understand these requirements, the business can implement an accurate and comprehensive data model, and it can achieve the information security objectives and business goals.
Shaneil Wilson says
In chapter 8 of the Modern Systems textbook, we learned about structuring system data requirements. Structural information about data is essential for automatic program generation. The most common format used for data modeling is entity-relationship (E-R) diagramming. A similar format used with object-oriented analysis and design methods is class diagramming. The purpose of the ERD is explain the characteristics and structure of data independent of how the data may be stored in computer memory. During requirements structuring, a data model represents conceptual data requirements for a particular system. Conceptual data model is captures the overall structure of the company’s data. After the logical design, the data model is refined before developing it into a relational data model. The relational data model is translated into physical database design and represents various business rules that govern the properties of data.
Zibai Yang says
The E-R diagram is also called the Entity Relationship Diagram, which represents entity types, attributes, and relationships. It is used to describe the conceptual model of the real world.
It is an effective way to describe the conceptual model of real-world relationships. It is a way of expressing the conceptual relational model. Use “rectangular box” to indicate the entity type, and write the name of the entity in the rectangular box; use “ellipse frame” or rounded rectangle to indicate the attribute of the entity, and use a “solid line segment” to connect it to the “entity type” of the corresponding relationship;
Use the “diamond box” to indicate the cause of the connection between the entity types, write the contact name in the diamond box, and use the “solid line segment” to connect to the relevant entity type, and at the same time mark the type of connection next to the “solid line segment.”
Jason Burwell says
The entity relationship diagram gives a snapshot of how these entities relate to each other. You could call it the blueprint that underpins your business architecture, offering a visual representation of the relationships between different sets of data.
In the diagram, entities are represented by boxes with lines linking them to various attributes, which describe the entity’s qualities or characteristics.
Everything links up according to the relationships between the entities – or how they interact with each other. Relationships are sometimes referred to as cardinalities, which describe the interactions numerically.