week 5 final 6211

8

EXTENDED ENTITY RELATIONSHIP

Extended Entity Relationship

Institution Affiliation

Date

The Extended Entity-Relationship model is used to design various data schemas. It is an approach that uses graphics for database designs. It is a high-level data model for a software system that defines data items and their relationships. In order to represent real-world items, an ER model is employed). An entity is made up of values and a set of properties. An entity is a creature or object in the real world that can be distinguished from its surroundings. The Enhanced Entity-Relationship (EER) Model is a high-level data model that adds to the Entity-Relationship (ER) model. EER Models support a more detailed design. EER Modeling is used for designing and modeling complicated databases.

An entity can have various attributes and properties that can be distinguished from other entities, and each property tends to have value and are relevant to the entity. The properties that determine the entity type are known as attributes. The properties that constitute entity type Student, for example, are Roll No, Name, DOB, Age, Address, and Mobile No. The attribute is represented by an oval in the ER diagram values can be assigned to each attribute. In the vast majority of circumstances, a single attribute has only one value. However, properties with multiple values are possible ( Al-Fedaghi, 2021). The constructs of an EER model are made up of entities, and these entities tend to have relationships. A relation contains data and indicates logical connections between two or more entities. Duplication of the data must be minimized; this is done to reduce the amount of storage required for data storage and prevent data conflicts that may arise due to numerous copies of the same data being saved. They are two major keys in the EER modeling include the primary key indicate relation’s unique identifiers. Employee numbers, social security numbers, and other numbers are examples. This ensures that each row is distinct. Foreign keys Identifiers that let a dependent relation refer to its parent relation (on the many sides of a connection) (on the one side of the relationship). The EER model maps the attributes and data, for instance, in customer’s data. The data may entail the customer ID, Customers address, and name.

Entity	Description	Attributes	Identifier
Customer	Customer purchases and makes an order from the company.	Surname, Customer ID, Address code	Code

Logical database designs

Database normalization allows related data to be grouped into a single table. Any unrelated data is grouped into other tables, forming a parent and child table. Normalization systematically dissects tables to remove data redundancy (repetition) and undesired characteristics such as insertion, updates, and deletion of information (Minh, and Hoang, 2018). It's a multi-step procedure for converting data into a tabular format and deleting data duplication from relation tables.

The 1NF, the first normal form, has no multivalued attributes, consists only of atomic values, and has no repeating groups. Anatomic value is a value that cannot be divided. This may include integers and dates. A repeated group indicates that a table has two or more two columns that are closely related.

Order ID	Order Date	Customer ID	Customer address	Product ID	Product price	Quantity
105	7/8/21	2	Boulder CO	7	1000	2
106	9/8/21	4	TX	5	700	5

When an order is made for the customer order 105 of an existing customer, customer data must be re-entered, causing duplication. When the data for customer order 106 is deleted, the information on the customer is lost on the price and quantity of the customer’s order. Changing the prices of orders will indicate that changes are also made in other multiple records.

A second normal form is a form that is used in the normalization of data. The principle of full functional dependency underpins the Second Normal Form (2NF). Relations with composite keys, or those with a primary key of two or more qualities, are subject to the Second Normal Form. A single-attribute primary key relation is automatically in at least 2NF. Update anomalies may affect a relationship that is not in 2NF. A relation must be in first normal form and contain no partial dependencies in second normal form. A relation in 2NF, if it has No Partial Dependency, means that no non-prime attribute (attributes that are not part of any candidate key) of the table depends on any suitable subset of any candidate key.

Order ID

Order Date

Customer ID

Customer Name

Customer address

Transitive dependencies

Third normal form

Order ID

Order Date

Customer ID

Customer ID

Customer Name

Customer Address

The transitive dependencies in the third normal from being removed.

DBMS

Data is any information or facts concerning an object in consideration. A database entails the collection of information and data. A database ensures that data can be easily accessed and managed through the collection of information and data. A database assists in the organization of data and also the storage of large volumes of data. A database management software is used for storing, modifying, and managing data, such as format, field names, and record and file structures. Users can use a DBMS to create their databases to meet their business needs. Database design also aids in developing, designing, implementing, and upkeep an enterprise data management system.

They are different types of databases used in DBMS products. These include hierarchical database, network database, relation database, and object-related database. Alphanumeric data is a generic data type that includes the use of numbers, letters, and images (Widianto, and Warmayudha, 2020). For instance, Oracle calls this type of data CHAR, used for fixed-length fields, and VARCHAR2 for variable field lengths. Microsoft Access defines this as a TEXT. It is always a variable length as they are no fixed length character data type in access.

Numeric Data

This includes this use of the number. Oracle uses p, s format for numbers. P indicates the total digits (precision) while s is the scale and indicates the digits after the decimal points. In some versions of Oracle, it allows the specification of numbers by type such as integers, long.MS Access has auto-number data, which is an integer and is automatically generated by the database.

Hierarchical database

Data is stored in a parent-children relationship node in a hierarchical database management system (hierarchical DBMSs) paradigm. In a hierarchical database, entries contain information about their groups of parent/child connections in addition to real data.

Physical design

Physical database design is the process of transforming a data model into a physical model. It is used to translate the logical description into technical specifications that ensure data is stored and retrieved. When considering the type of physical database design, there is a need to include some factors. Transactions and Queries

It is important to understand and indicate the kind of transactions and queries that will be run and the use of the database. The files that will query access indicate selection conditions to be specified for the query, in the transactions the files need to update, operation type to be performed on files, and attributes of data that need to be modified.

Frequency analysis allows the compilation of the expected frequency of each query/transaction, and time constraints offer performance contracts. These constraints place priorities in the attributes. The attributes are used in the query have the highest priority.

Update Frequency – If, for instance, a file needs to be regularly updated, there is a need to maintain a minimum number of paths for access. This is because updating the files slows down the operation of the database.

Uniqueness Constraints –Every key attribute must have an index. The presence of an index makes the search of information and data easier and allows it to be manageable. The index makes the search easier as it ensures the use of a unique code that distinguishes it from others, and it is unique when the uniqueness constraints are checked. This is because the attribute values exist within the indexes nodes.

In this case, there is a need to ensure that each customer’s order information is unique. This allows the easy identification of the orders and the customers. Also, the time contrast indicates the performance constraints, and these ensure there is prioritization on the customers according to the time when the purchase was done.

Data Architecture

Data architecture comprises models, policies, and standards that indicate and give the data that should be collected. It also specifies how data in data systems and organizations should be stored, organized, integrated, and used. Organizations must have reliable data to achieve strong business results, and the usage of that data must be managed by policy and monitoring. In an organization, data governance encompasses data decision-making, administration, and responsibility. A data governance team is frequently formed to ensure that data is managed efficiently and effectively and inculcate data quality. Data governance initiatives are intended to help an organization prepare rules and regulations and deal with any data-related concerns that may arise.

Data Governance

Identify roles and responsibilities.

It is important that determine the strategy for having an effective data governance structure. This strategy can be written with the assistance of the stakeholders and that are involved in the project. Identify the data personas

.

The information needs of data consumers influence the technology environment. It is important to include the people responsible for creating, storing, and updating data within the enterprise.

Determine Information Requirements

Engage the consumers in understanding their business strategy and solicit their business requirements for data.

Evaluation of information risks

It includes identifying and interpreting the data governance directives and how it relates to the handing, management, and protection of data.

Ensure Consistency in Data Collection and workflows

Establish Data controls

It is important to define the key controls, metrics, and data thresholds. It develops the reporting process around and how it is used.

Identifying Authoritative data sources

Establish policies and standards

The standards and policies are used to indicate the standards of the data architecture and what is required.

References

Al-Fedaghi, S. (2021). Conceptual Data Modeling: Entity-Relationship Models as Thinging Machines. arXiv preprint arXiv: 2109.14717.

Bernal, J. N., Rodriguez, J. P., & Portella, J. (2021). DBMS and Oracle Datamining.

Bourou, D. A., Schorlemmer, M., & Plaza, E. (2021). Modeling the sense-making of diagrams using image schemas. In Proceedings of the Cognitive Science Society (Vol. 43, No. 43).

Minh, V. H. L., & Hoang, Q. (2018). Transforming an extended entity-relationship model into OWL ontology in temporal databases. Journal of Science and Cybernetics, 34(1), 77-96.

Widianto, S. R., & Warmayudha, I. P. E. (2020). HSQL Database. Jurnal Mantik, 4(3), 1717-1721.