What is Reverse Engineering a Data Model? Reverse Engineering is a process or function to create a logical and physical data model by extracting information from an existing data source. You may either create a physical data model or logical data model or combination of both. Data Source may be oracle data base or MS…
How to create DDL Scripts from Data Model? Open the physical data model “Data_Modeling_Relationship.txl”. Click menu Model/Verify Model. A new window will be opened. Check the appropriate objects like entities, functions, packages, materialized views, relationship, synonyms, data types etc which are listed in the new window. Click “Verify” button on the bottom of the page….
During the development cycle of data model, several changes/updates may take place over time depending upon the needs and requirement of that project. As and when required, different data model versions will be created with little or more changes between them. At one point of time, one may require to know the exact differences between…
Relational | Dimensional Data Modeling: Relational Data Modeling is used in OLTP systems which are transaction oriented and Dimensional Data Modeling is used in OLAP systems which are analytically based. In a data warehouse environment, staging area is designed on OLTP concepts, since data has to be normalized, cleansed and profiled before loaded into a…
Logical | Physical Data Modeling: When a data modeler works with the client, his title may be a logical data modeler or a physical data modeler or combination of both. A logical data modeler designs the data model to suit business requirements, creates and maintains the lookup data, compares the versions of data model, maintains…
Logical and Physical Data Modeling Objects: To become a data modeler, you need to understand the concepts of a database. Before proceeding further, please visit our topics listed under the section “Database and Data Modeling” to get a fair knowledge about the database. The following table briefs about the objects used in constructing the data model…
Analysis of Data and creating Tables & Relationships: Usually in a data model, Tables (Entities) looks like rectangular or square type boxes, which contains columns(attributes) and these tables are connected by lines (relationships). Identifying relationship and Non-Identifying relationship are two types of relationships. Based on cardinality, relationship are broadly classified into one to one relationship, one…
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…
SuperType and SubType in Data Modeling: At times, few entities in a data model may share some common properties (attributes) within themselves apart from having one or more distinct attributes. Based on the attributes, these entities are categorized as Supertype and Subtype entities. Supertype is an entity type that has got relationship (parent to child…
Dimensional Data Modeling comprises of one or more dimension tables and fact tables. Good examples of dimensions are location, product, time, promotion, organization etc. Dimension tables store records related to that particular dimension and no facts (measures) are stored in these tables. For example, Product dimension table will store information about products (Product Category, Product…
