Crack Erwin Data Modeler Standard

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If you're looking for Data Modeling Interview Questions for Experienced or Freshers, you are at right place. There are lot of opportunities from many reputed companies in the world. According to research Data Modeling has a market share of about 15.43%.

So, You still have opportunity to move ahead in your career in Data Modeling Architecture. Mindmajix offers Advanced Data Modeling Interview Questions 2019 that helps you in cracking your interview & acquire dream career as Data Modeling Architect.

Are you interested in taking up for Data Modeling Certification Training? Enroll for Free Demo on Q. What is data modeling? A data model is a conceptual representation of business requirement (logical data model) or database objects (physical) required for a database and are very powerful in expressing and communicating the business requirements and database objects. The approach by which data models are created is called as data modeling. What does data model contain? Logical Data Model: Entity, Attributes, Super Type, Sub Type, Primary Key, Alternate Key, Inversion Key Entry, Rule, Relationship, Definition, business rule, etc Physical Data Model: Table, Column, Primary key Constraint, Unique Constraint or Unique Index, Non Unique Index, Check Constraint, Default Value, Foreign Key, comment etc.

What is a logical data model and logical data modeling? A logical data model is the version of a data model that represents the business requirements (entire or part of an organization). This is the actual implementation and extension of a conceptual data model. Logical Data Models contain Entity, Attributes, Super Type, Sub Type, Primary Key, Alternate Key, Inversion Key Entry, Rule, Relationship, Definition etc. The approach by which logical data models are created is called as logical data modeling.

What is a physical data model and physical data modeling? Physical data model includes all required tables, columns, relationship, database properties for the physical implementation of databases. Database performance, indexing strategy, and physical storage are important parameters of a physical model. The important or main object in a database is a table which consists or rows and columns. The approach by which physical data models are created is called as physical data modeling.

What is the difference between a logical and physical data model? 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 change log, generate reports from data model and whereas a physical data modeler has to know about the source and target databases properties. A physical data modeler should know the technical-know-how to create data models from existing databases and to tune the data models with referential integrity, alternate keys, indexes and how to match indexes to SQL code.

It would be good if the physical data modeler knows about replication, clustering and so on. What is a table (entity)? Data stored in form of rows and columns is called as table.

Each column has datatype and based on the situation, integrity constraints are enforced on columns. What is a column (attribute)?