physical database model

Understanding Physical Database Infrastructure {1}

by Allen D
Data warehouse experts are responsible for creating a bridge between business requirements for information and technological resources at hand to better process big data. In order to make this happen, database architects and business analysts meet to translate the company’s abstract data into logical models that colleagues can easily make sense of. In the article, “Building a Best-Fit Data Warehouse: Why Understanding Physical Database Structure Matters”, John O’Brien identifies key issues that challenge the CPU power, disk space and connectivity balances of a typical corporate network in processing big data. The article also introduced four architecture models that data architects use to structuralize business intelligence. read more...

Logical vs. Physical Modeling {3}

by Kathy S
The two authors of this article start off by declaring that data modeling serves as a link between business needs and system requirements. They stress that if we are going to work with databases, it is important to understand the difference between logical and physical modeling, and how they relate to each other. First, Logical Modeling deals with gathering business requirements and converting those requirements into a model. Also, it involves gathering information about business processes, business entities, and organizational units. After, diagrams and reports are produced (entity relationship , business process, and process flow diagrams). According to the authors, it’s important to note that logical modeling affects the direction of database design and indirectly affects the performance and administration of an implemented database. More options become available when time is invested performing logical modeling. Next, the authors go into Physical modeling. Physical modeling involves the actual design of the database according to the requirements that were established during logical modeling. Physical modeling deals with the conversion of the logical, or business model, into a relational database model. During physical modeling, objects are created based on everything that was defined during logical modeling. Other objects like indexes and snapshots can be defined during physical modeling. Physical modeling is when all the pieces come together to complete the process of defining a database for a business. The authors conclude that the importance of understanding the difference between logical and physical modeling helps us to build better organized and more effective database systems. read more...

Moving from Logical to Physical {1}

by Kevin S
As we prepare to take the next step in database design, it is important to relate the new material with what we have already learned. In the article “Logical Versus Physical Database Modeling”, authors Ryan Stephens and Ronald Plew do just that. They describe data modeling as “a link between business needs and system requirements”. They summarize the logical model deliverables as including the ERD, Business process diagrams, and user feedback documentation. Where as the deliverables for physical modeling includes server model diagrams and its feedback documentation. read more...

Create An Effective Data Model For Your Database {1}

by Toan T
This article talks about how a newly developer such as myself that have never build database before can build an actual database that is functional and efficient at the same time. Database development of today is somewhat different from what have been done in the past, companies are often cutting costs which mean that the modeling process might require heavy modifications. This article provides the fundamental concepts that can help anyone create a data model that fits his/her needs.
There are three stages to developing a database: Planning, Design and Deployment. In the real world when a database will be used for a single application, planning usually receive less attention and most of the work lies within the design and deployment phases. The article also heavily emphasize on three concepts that would help create a more logical quality to the data that would promote re-usability. Conceptual Data Model or CDM for short is a effective data model that heavily emphasized on business rules. This usually includes ERD that help describe the business steps that occur within an organization. In other words, data is created and attributes are identified. The second model is Logical Data Model where the database involving CDM is taken and get translated into an empirical layout of the data. This is when the all the data that was from CDM get transferred and then process by applying them into a normalized layout. The last model is the Physical Data Model where everything that was developed in the last two models get brought together into a final layout of tables where columns, index and constraints are defined. read more...