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LOGICAL data Model - Software Data engineering
The document discusses logical data modeling. It defines a logical data model as establishing the structure of data elements and relationships independent of physical implementation. It notes logical data models serve as a blueprint for used data. The document outlines key components of logical data models including entities, relationships, and attributes. It also discusses characteristics such as being independent of database systems and modeling business requirements. Overall, the summary provides a high-level overview of the key topics and purpose of logical data modeling covered in the document.
LOGICAL data Model - Software Data engineering
- 1. LOGICAL DATA MODEL December 2023 ABDULAHAD, AAHADQJ@GMAIL.COM Data Modelling 101
- 2. WHAT IS LOGICALDATA MODEL A logical data model establishes the structure of data elements and the relationships among them. It is independent of the physical database that details how the data will be implemented. The logical data model serves as a blueprint for used data. The logical data model takes the elements of conceptual data modeling a step further by adding more information to them. The logical data model incorporates all of the elements of information that are vital in the running of the day to day business.
- 3. WHAT IS LOGICALDATA MODEL
- 4. NEED OF LOGICALDATA MODEL Given that data embodies the most crucial aspect of any application, program, or system, quality data processing and storage systems must be built upon a strong and accurate underlying data structure. A sound data structure gives application developers the freedom to design the best possible user interface, processing system, or statistical analysis and reporting set-up. No matter how elegant or technical your system, it has to meet requirements, follow rules, and serve the purposes of the business or enterprise it is built for—or else it is of no practical use. Therefore, logical data modeling brings together the two most vital basics of application development: Business requirements 1. Quality data structure 2.
- 5. COMPONENTS OF A LOGICALDATA MODEL 01 ENTITIES Entities: Each entity represents a set of things, persons, or concepts relevant to a business 02 RELATIONSHIPS Every relationship represents an association between two of the above entities 03 ATTRIBUTES Each attribute is a descriptive piece, characteristic or any other information that is useful to further describe an entity
- 6. CHARACTERISTICS OF ALOGICAL DATA MODEL A logical data model can describe the data needs for each individual project. Yet, it is designed to seamlessly integrate with other logical data models should the project demand it to do so. A logical data model can be developed and designed independently from the database management system. The type of database management system does not affect it that much. Data attributes contain data types with exact length and precisions. In logical data modeling, no primary or secondary key is defined. At this level of data modeling, it is required to verify and tweak connector details that were set prior to defining relationships. A logical data model is like a graphical representation of the information requirements of a business area. It is not a database or database management system itself. A logical data model is independent of any physical data storage device, such as a file system. A logical data model must be designed to be independent of technology, so as not to be affected by the rapid changes in technology.
- 7. CHARACTERISTICS OF ALOGICAL DATA MODEL A logical data model can describe the data needs for each individual project. Yet, it is designed to seamlessly integrate with other logical data models should the project demand it to do so. A logical data model can be developed and designed independently from the database management system. The type of database management system does not affect it that much. Data attributes contain data types with exact length and precisions. In logical data modeling, no primary or secondary key is defined. At this level of data modeling, it is required to verify and tweak connector details that were set prior to defining relationships. A logical data model is like a graphical representation of the information requirements of a business area. It is not a database or database management system itself. A logical data model is independent of any physical data storage device, such as a file system. A logical data model must be designed to be independent of technology, so as not to be affected by the rapid changes in technology.
- 8. DATA MODELING TECHNIQUES EntityRelationship (E-R) Model UML (Unified Modelling Language) Logical data modeling belongs to the entity relationship model, built using an Entity Relationship Diagram (known as ERD), a standard modeling technique used as a communication tool by data modelers worldwide. Within it are the complete set of business requirements but not technical components.
- 9. DATA MODELING TECHNIQUES EntityRelationship (E-R) Model UML (Unified Modelling Language) Logical data modeling belongs to the entity relationship model, built using an Entity Relationship Diagram (known as ERD), a standard modeling technique used as a communication tool by data modelers worldwide. Within it are the complete set of business requirements but not technical components.
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- 11. ADVANTAGES OF ALOGICAL DATA MODEL As data remains stable over time, a logical data model is also a stable one and highly conducive to data re- use and physical data sharing, which ultimately leads to reduced storage of redundant data. Components of a logical data model can be recycled, re-used, and adapted as more teams weigh in with their (often changing) needs. Costs associated with building and maintaining a logical data model are offset in the long run by the advantages it confers, not least by identifying and integrating all business needs and rules at the outset. Components of the building process, namely, design, coding, testing, and deployment go faster, as a direct result of the integration and clarification of business rules. Having a logical data model in place makes it easier, and therefore cost effective, to make changes, correct mistakes, or enter missing data during the development life cycle itself prior to implementation. User requests for making changes can be minimized by being proactive. Logical data models can be used for impact analysis, as each and every business process plus rule is connected within it. As objects in the logical data model bear textual definitions in business language, it makes it easier to maintain and access system documentation.
- 12. LOGICAL DATA MODEL- EXAMPLE
- 13. LOGICAL DATA MODEL- EXAMPLE
- 14. HOW DOES ALOGICAL DATA MODEL WORK? Logical data models serve as an abstraction layer, defining the relationships between different data elements, entities, and attributes. Unlike a physical data model, which is specific to a particular database system, a logical data model focuses on the business concepts and rules that govern the data.
- 15. HOW DOES ALOGICAL DATA MODEL WORK? Entities, Relationships, And Attributes Entities are the fundamental building blocks of a logical data model, representing objects or concepts— customers, products, or orders, for example. Relationships define how these entities are connected or associated with each other, while attributes describe the characteristics or properties of the entities. In the example below, the logical data model illustrates a set of related tables connected by primary key (PK) and foreign key (FK) relationships.
- 16. HOW DOES ALOGICAL DATA MODEL WORK? Normalization Normalization is a key concept in logical data modeling that involves the organization of data to reduce redundancy and improve data integrity. The goal of normalization is to eliminate data anomalies—update, insert, or delete anomalies, for example—by structuring the data in a way that minimizes duplication. The processes and stages of normalization involve breaking down large tables into smaller, more manageable tables and establishing relationships between them.
- 17. BENEFITS OF LOGICAL DATAMODELING Thynk Unlimited 01 Improved Data Comprehension Provides is a clear and comprehensive view on data. By mapping out the relationships between different data elements in easy-to- understand/minimal notation, a range of stakeholders 02 Better Communication Logical data models serve as the common language for bridging the communication gap among various stakeholders involved in the data management process. 03 Change Management Change is of course inevitable, and logical data models—when designed well—allow organizations to adapt and evolve more efficiently and with greater agility. From accommodating new business rules and modifying existing processes to integrating new 04 Enhanced Data Quality By promoting normalization and adherence to data modeling best practice, logical data models contribute to improved data quality across an organization’s data estate. Logical data modeling practices like reducing redundancy and enforcing relationships between entities helps to maintain data integrity, as well as minimize errors and inconsistencies caused by duplicate or conflicting information.
- 18. LOGICAL DATA MODEL- EXAMPLES Logical data models can be used in a wide range of applications. The following examples show how the logical data model paradigm can be used from the perspective of different domains. Healthcare Management—In a healthcare management system, a logical data model might include entities such as “Patient,” “Doctor,” “Appointment,” and “Medical Record.” Relationships could include “Doctor treats Patient,” “Patient schedules Appointment,” and “Medical Record corresponds to Patient.” Attributes for the “Patient” entity might include “PatientID,” “Name,” and “Date of Birth.” Financial Services—In the financial services sector, a logical data model could encompass entities like “Account,” “Transaction,” and “Customer.” Relationships might include “Customer owns Account” and “Transaction involves Account.” Attributes for the “Account” entity could include “AccountID,” “Balance,” and “Account Type.”
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