Data Modeling Development Cycle Following are the important phases in the Data Model Development Life Cycle. Gathering Business Requirements Conceptual Data Modeling Logical Data Modeling Physical Data Modeling Development of the schema or the database Maintenance of the data model as per the changes. 1. Gathering Business Requirements – First Phase: Data Modelers have to…
Data Model Versioning | Concepts | Advantages | Uses: Data Model Versioning is the process of assigning either unique version names or unique version numbers to different stages of a data model. Data Modeling tools may have this versioning facility in their software itself and versions of data models may be stored in their repository. The…
What is a Data Model Repository? A data modeling repository is a storage area, where metadata of a data model is stored. The data stored is different from the software perspective, organization’s perspective and usage perspective. Repository can be stored any where; either in a data base or locally within any system. Example: ETL Repository…
From Data Modeling tools, reports can be easily generated for technical and business needs. The reports that have been generated from logical data model and physical data model are called as business reports and technical reports respectively. Most of the data modeling tools provide default reports like subject area reports, entity reports, attribute reports, table…
Data Modeling standardization has been in practice for many years and the following section highlight the needs and implementation of the data modeling standards. Standardization Needs | Modeling data: Several data modelers may work on the different subject areas of a data model and all data modelers should use the same naming convention, writing definitions…
Data Modeler Role: Data Modelers fall into two major categories of Logical or Physical Data Modelers depending upon the role they play in developing Logical or Physical data models. Based on organization needs, data modelers only do logical data modeling or physical data modeling or combination of both. Nowadays, organizations prefer to hire data modelers,…
Steps to create and maintain a new data model from business requirements: These are the general guidelines to create a standard data model and in real time, a data model may not be created in the same sequential manner as shown below. Based on the enterprise’s requirements, some of the steps may be excluded or…
Why to build or create a data model? To avoid redundancy of data in a OLTP database. In Data Warehousing, data from source systems can be transformed as per the rules and loaded into target tables. In Data Warehousing, you can do data profiling by cleaning the data from source systems and load that into…
What is a Data Model? A Data model is a conceptual representation of data structures (tables) required for a database and is very powerful in expressing and communicating the business requirements. Data Modeling Overview: A data model visually represents the nature of data, business rules governing the data, and how it will be organized in…
