Data Lake Data Modeling Training – Data Vault Approach

About the Training:

This course is focused towards the fundamentals and not the detailed one in Data Vault Data Modeling. However, this course will help you to clear interviews, to understand Data Vault Data Modeling fundamentals to step into Data Lake Environment.

If you are interested, please approach or 91-90801 57239.

  • Course: Data Lake Data Modeling Training – Data Vault Approach
  • Start Date: June 3rd, 2023
  • Training Fess: 200 us dollars or INR 16,000/
  • Training Hours: 10 plus
  • Weekend: Saturday 7 pm IST to 9.30 pm IST and Sunday 7 pm IST to 9.30 pm IST
  • Trainer: Working as a Data Modeler in Azure Data Lake Environment – Data Vault Approach.
  • Online Meeting Software: Go to Meeting
  • Online Class Reference Documents: Will be provided.
  • Online Class Videos: Will be provided, life time Access.

Data Vault Data Modeling Training:

  • Overview: How Business Analysts get data for data modeling?
  • Overview: What is Bus Matrix in Azure Data Lake?
  • What are the components in a Bus Matrix?
  • Jira Overview : How Scrum Masters create user stories for a particular Requirement?
  • Overview: How Business Analyst write about ingestion of data in Confluence?
  • Overview: What is DMD? Data Mapping Diagram?
  • Overview: What format is followed for meta data creation?
  • Jira Overview: What format is followed for Data Ingestion User Story?

Agile Scrum | Data Modeler’s Activities:

  • Understand Bus Matrix and Tables from the daily AGILE sprint stand up call and documents.
  • What is done in: Scrum Planning, Daily Sprint, Sprint Retrospective Meeting, Parking Lots Meetings?
  • How to Understand user stories, create sub tasks for the user stories, complete it and assign sub tasks to other teams.
  • What to do with incomplete tasks in Jira?

Data Vault Data Modeling:

  • What is Data Vault?
  • What is Raw Vault?
  • What is Business Values?
  • Why we need to go for Data Vault rather than our OLTP and OLAP Data Modeling?
  • How to create Data Modeling Standards in Raw Vault and Business Vault.
  • Hash Key algorithms.
  • How to create Raw Vault Data Models in Excel spreadsheet?
  • How to Create Raw Vault Data Model with Hubs, Satellites, and Links in Excel?
  • What is Reference Table, Bridge Table, and PIT tables?
  • How Raw Vault Data from Excel is imported into Erwin?
  • Develop Business views from Data Vault.
  • Create Star Schema (Combine Hubs, Satellites, and Links.) Models in Information Mart.
  • Create SQL Queries(Representative SQL based on Logic) for the Data Loading Team to populate the Tables in Azure Environment.
  • Create Business Views based on Information Mart for Business Users for a new environment

New Features in Erwin Release 2020 R1

  • Use ‘Active’ Model Templates to facilitate reusable modeling metadata and to implement/enforce enterprise standards
  • Erwin Data Modeler is now certified to work with: Db2 z/OS v12
    SQL Server 2019
    PostgreSQL v9.6.15, v10.10 and v11.5
    Oracle 18c (18.3)
  • Erwin Data Modeler now supports the new features and capabilities offered in Db2 LUW 11.1 like: Storage Group object support has been added.
    Table properties for all three types (Permanent, Global Temporary, and Nickname) have been updated. Also, Index and XML Index support has been enhanced.
    Tablespace properties have been updated to support Storage Space Name and Data Tag.
    Materialized query table properties have been enhanced.
  • Erwin DM Scheduler: Enables users to define and schedule database reverse engineering (REDB) tasks in advance
    Minimizes workstation contention by allowing modelers to plan for and run REDB tasks when resources are available
  • Overall modeler productivity has been enhanced via new product functionality and workflows: A “quick” compare option set and “speed” option
    Supertype-Subtype transformation updated to retain separate logical and physical constructs for Identity and Roll-Up option selections
    Deletion of a relationship offers modeler the option of converting migrated FK attribute(s)/column(s) into child entity/table owned attribute(s)/column(s)
    Mart OPEN dialog now displays number of entities, attributes and relationships
    Mart and mart report performance has been significantly improved
    Database “Target server” dialog can be accessed by clicking the database name displayed on the physical model status bar
  • Naming Standards enhanced to fully support physical-to-logical name mapping
  • Users defined in Azure Active Directory can now connect to the Mart from erwin Data Modeler.
  • Enhanced product security measures include: Third-party components upgraded:
    Tomcat v9.0.27
    OpenSSL 1.1.1c
    AdoptOpenJDK (build 11.0.3+7)
  • Erwin Data Modeler now offers an automation option for Reverse Engineering and Forward Engineering through the Erwin API.
  • Erwin Data Modeler includes flexible extended notes on all object types that can be: compared, searched, and edited using the Bulk Editor
    reported via the Report Designer
    managed using the erwin API
  • Erwin SCAPI has been extended to support the application of naming standards.
  • Erwin Data Modeler provides “native” support for Hadoop Hive as a database target – including AVRO files!
  • Licensing improvements include: Silent Install
    Option to “hide” Licensing dialog
    Support for proxy connections to the License/Activation server
    Optional network domain name and subnet IP-based usage restrictions
    erwin Data Modeler “edition”-based licensing
    The ability to “borrow” (Long Term Check Out) cloud-based concurrent licenses
  • Collaboratively administer the Workgroup Edition mart using our web-based Mart Administration utility Session (Offline/Disconnect) Management
    Security (User/Role) Management
    AD Authentication (via LDAP)
    Permission/Authorization Management
    Model Locking
  • Collaboratively administer the Workgroup Edition mart using our web-based Mart Administration utility Session (Offline/Disconnect) Management
    Security (User/Role) Management
    AD Authentication (via LDAP)
    Permission/Authorization Management
    Model Locking
  • Erwin Data Modeler supports a wide variety of reports from a mart, including: administrative
    model object count reports
  • The erwin Data Modeler (DM) User Interface has been revamped to include the following: A Microsoft “Office-like” ribbon-based appearance
    UI themes, font sizes, and component direction settings
    Tabbed and “side-by-side” diagram window arrangement option
    A “Quick Access” toolbar
  • Erwin Data Modeler supports both online and local product documentation and help.
  • Erwin Data Modeler has added “native” support for Redshift as a database target.

  • Report Designer includes the ability to create customized report filters and properties using erwin Data Modeler’s TLX scripting language
  • Erwin Data Modeler supports new features and capabilities offered in SQL Server like: Always Encrypted columns
    Dynamic Data Masking
    Temporal tables
    Memory Optimized Table
    Natively compiled Stored Procedures
  • Erwin Data Modeler supports new features and capabilities offered in SQL Server like: Always Encrypted columns
    Dynamic Data Masking
    Temporal tables
    Memory Optimized Table
    Natively compiled Stored Procedures
  • User enhancements and modeling improvements include: A new option has been added to allow modelers to enforce Relationship Nullability Rules
    A new option has been added to allow modelers to enforce Supertype-Subtype relationship rules
    Oracle 12c support for 128 character TABLE and COLUMN Names and PostgreSQL support for 63 character TABLE and COLUMN names
    New support added for relationship cardinality ranges (for example, 1..5)
    New “Forward Engineering” wizard
    Ability to tag ATTRIBUTES/COLUMNS as PII
    Support for Hive VIEW Partitions
  • Erwin Data Modeler is offered as a native 64-bit application with access to sufficient memory to complete operations on large models (A 32-bit option is still available).

Data Modeling Interview Question and Answer Videos

Video Tutorial 1:

What is a Data Model and Data Modeler Responsibilities?

What’s in it: Data Model, High Level Data Modeler Responsibilities along with images of a conceptual data model, logical data model and physical Data Model is explained using Erwin Data Modeling Tool.

Video Tutorial 2:

Explain Data Modeling Development Life Cycle?

What’s in it: This question is asked by the Interviewers. Our video explains step by step process in Data Modeling Development Life Cycle. This life cycle is common for RDMS Data Modeling and Dimensional Data Modeling.

Video Tutorial 3:

What is an ER Diagram?

What’s in it: ER Diagram also know as Erwin Relationship Diagram is explained with a data model created by using Erwin Data Modeling Tool. Primary Key Constraint, Composite Primary Key Constraint, Foreign Key Constraint, Composite Foreign Key Constraint are explained here in this Data Modeling Video Tutorial.

Video Tutorial 4:

What is a Conceptual Data Model?

What’s in it: This is the first phase in designing the data model in the Data Modeling Development Life and is explained in Detail with image of Erwin Data Model.

Video Tutorial 5:

What is a Logical Data Model?

What’s in it: The is second phase in designing the data model in the Data Modeling Development Life Cycle and is explained in details

Video Tutorial 6:

What is the difference between a Logical Data Model and Physical Data Model?

What’s in it: The differences between Logical Data Model and Physical Data Model is tabulated and explained with the help of a data model created from the Erwin Tool.

Video Tutorial 7:

What is an Entity and Attribute?

What’s in it: Entity and Attribute are explained with a Diagram.

Video Tutorial 8:

What is Identifying and Non-Identifying Relationship?

What’s in it: Identifying and Non-Identifying Relationship are explained with the help of a small data model drawn from Erwin Data Modeling Tool. Difference between those two are also explained.

Video Tutorial 9:

What is Forward Engineering & What is Reverse Engineering?

What’s in it: Forward Engineering, Reverse Engineering, SuperType and SubType are explained.

Video Tutorial 10:

What is Data Model Meta Data & Data Model Repository

What’s in it: Data Model Meta Data & Data Model Repository are explained in this video tutorial.

Video Tutorial 11:

What is the process to create a Data WareHouse Schema and What are the steps involved in designing the data mart?

What’s in it: This video explains important points in designing the Data Mart and Data Warehouse Schema.

Video Tutorial 12:

What is Dimensional Data Model and a Star Schema?

What’s in it: This video explains the basics of Dimensional Data Model and Schema with OLA use case as the example.

Video Tutorial 13:

What is ETL? / What is Datawarehouse? / What is DataMart?

What’s in it: Basics of ETL, Datawarehouse and Datamart are explained in this Data Modeling Video Tutorial.

Video Tutorial 14:

What is Check Constraint? / What is a Sequence? / What is an Index?

What’s in it: Brief explanation of Check Constraint, Sequence, and Index is explained.  Also NULL values in Unique constraint are explained.  The above topic is an important question in the Data Modeling Interview..

Video Tutorial 15:

What is OLTP Data Modeling? / What are the different types of constraints? / What is an Unique Constraint?

What’s in it: Brief explanation about OLTP data modeling and constraint. This is an important question in Data Modeling Interview.

Video Tutorial 16:

What is a Foreign Key Constraint? / What is a composite Foreign Key constraint?

What’s in it: Foreign Key Constraint is explained in a detailed manner by taking an example from IBM.

Video Tutorial 17:

Erwin Data Modeling Interview Questions – Part 1

What’s in it:

This video helps with the list of interview questions that can be asked in creating :
Conceptual data model by Erwin.
Logical data model by Erwin.
Physical data model by Erwin.

Video Tutorial 18:

Dimensional Data Modeling Interview Questions – Part 1

What’s in it:

These Dimensional Data Modeling Questions are related to Data Warehouse and Data Mart.
When you work as an ETL developer or BI developer, these questions will be asked in the interview.

Data Modeling Videos For Sale

A step-by-step Data Modeling Video Tutorials to learn/design: OLTP/Dimensional Data Modeling with Data Model Deliverable.

Following is the Syllabus for the Data modeling Videos:

1 – Introduction about Data Model

  • What is a Data Model?
  • What is a Logical Data Model?
  • What is a Physical Data Model?
  • What is the difference between Logical and Physical Data Model?
  • Salary of a Data Modeler
  • What are the other titles for Data Modeler?
  • Duties and Responsibilities of a Data Modeler
  • Data Modeling Development Life Cycle
  • Data Modeler Deliverable

2 – Conceptual, Logical, Physical Data Model

  • Difference between a Domain and a Datatype
  • What is ER Diagram (Entity Relationship Diagram)?
  • What is an Entity? And Entity Naming Convention Rule.
  • What is an Attribute?
  • What must be included in Conceptual Data Model?
  • What must be included in Logical Data Model?
  • What must be included in Physical Data Model?
  • How DDL scripts looks like?

3 – Oracle Database 12. 1..0.2.0

  • How to connect to Oracle Database

Examples in Oracle:

  • How to create table, drop table and alter table
  • How to insert records into table
  • What is Tab and commands like Describe, Clear Screen, Commit and To-Date Function
  • How to create primary key, composite primary key, check constraint, not null constraint, unique constraint, foreign keys, composite foreign keys?

4 – Oracle database

  • Insert, Update, Delete Statement
  • Select Statements
  • Aggregate Functions (Group By, Having, Count)
  • Where Clause, Sub Query
  • Operators (IN, NOT IN, >, <) etc.
  • Boolean Operators AND, OR NOT
  • Commit, Rollback
  • Create Index, Drop Index
  • How to use System Tables: All_Ind_Columns, User_Constaints, User_Cons_Columns
  • and much more

5 – Data Modeling Concepts

  • What is a Data Model?
  • Entity Relationship Dagram
  • Logical Data Model
  • Identifying Entities
  • Datatype
  • Basic Attribute, Deriving Attribute, Multivalued Attribute


  • “Key, Unique Key, Identifier, Super Key, Trivial Super Key, Candidate Key,
  • Primary Key, Natural Key (Business Key, Domain Key) Alternate Key, Foreign Key, Surrogate Key”
  • What are the interview questions related to keys?
  • Examples to understand keys

6 – Data Modeling Relationship

  • Cardinality
  • Notation
  • Exactly One, Zero or one, One or more, Zero/One/More, More than one

Relationship Cardinality:

  • One to One, One to Many, Many to Many
  • Optionality
  • Relationship Cardinality and Optionality Notations
  • How to read the relationships?
  • Not Null Constraint

7 – Relationships in an OLTP Data Model using Erwin

  • Introduction by the trainer and students
  • Introduction about data model
  • Use Case: H1B Applicant Data Model
  • Identifying lookup table and transaction tables
  • Creation of data model using Erwin
  • creation of entity and primary keys in Erwin
  • Creating conceptual data model
  • Identifying null and not null
  • Identifying cardinality
  • Identifying one to one, one to zero/one/many, one to one/many
  • Non identifying relationship

8 – Relationships in a Data Model using Erwin

  • Many to Many relationship
  • How to create a Conceptual Data Model
  • Identifying relationship
  • How to handle composite primary keys in a data model
  • Why data analysis is important?
  • Self-Referential Integrity Relationship
  • Cardinality
  • How to create a Logical Data Model
  • How to create a Lookup Script?
  • How to do forward engineering (schema generation)?

9 – SuperType, SubType

  • Generalization with subjoin subtypes (Mutually exclusive)
  • Attribute Inheritance
  • Disjoint (Exclusive) Constraint
  • Overlapping (Inclusive) Constraint
  • Participation (Completeness Constraint)
  • Specialization (Top Down Approach)
  • Generalization (Physical Data Model)
  • Super Type Implementation (Single Table)
  • Sub Type Implementation
  • When we should use supertype implementation?
  • When we should use subtype implementation?

10 – Normalization Concepts

Business Process: What happens in a clinic with doctors patients visiting fee and medicines provided?

  • Normalization Intro
  • What is Normalization? Why Normalization is required?
  • What is redundancy?
  • Insert, Update, Delete Anomaly

Data Analysis of a clinic (clinic, doctor, patient, fees and medicines provided) – Case Study

  • Functional Dependency
  • 1NF, 2NF, 3NF

11 – Normalization – Data Analysis of Student data (student, course, grade, instructor)-

Business Process: What happens in student, course, instructor relationship?

  • Create tables in 1 NF, 2NF, 3NF with the business rule “1 course can be taught by only one instructor”
  • How to modify the data model when business rules change “1 course can be taught by more than one instructor”

Normalization – Small Retail Sales Data – 1NF, 2NF, 3NF

Business Process: How to analyze retail sales data

  • Data Analysis of a small Retail Sales Data which consists of order, payment, shipment, federal tax, state tax, billing, items, items ordered, item name, total price, ordered quantity and how to handle multiple payment for an order

12 – UBER-OLA OLTP Data Model – Sample Case Study

  • Business Process: How to store Rider Information and how to query the data


  • How to build conceptual data model?
  • How to build source schema (OLTP)?
  • How to build target schema (Dimensional)?
  • How to aggregate the data on daily basis and monthly basis (olap analysis)?
  • How to calculate the daily trip cost?
  • How to find out the drivers who cancelled the trip?
  • How much money driver made?
  • How to run different queries on top of this data model?
  • Uber carpool scenario

Business Process: How to capture Training Center Employee/Student/Course Information/fees/training session

  • How to capture the products that are explained?
  • How to capture the training videos that are sold?
  • how to implement identifying, non-identifying relationships?
  • How to implement super type and sub type?

14 – Cloud OLTP Data Model – Sample Case Study

Business Process: How to store the online sales for a product? – Microsoft Office 365 as example from Web browser Application

  • Explanation of office 365 application
  • Explanation of table creation
  • How to capture users, plans, option and subscription

15 – How to create a Staffing OLTP Data Model? – Sample Case Study

Business Process: How to hire a candidate.

16 – US Banking OLTP Data Model – Sample Case Study

Business Process: How to store financial and nonfinancial transactions for a Checking Account?

17 – US Mortgage OLTP Data Model

  • Business Process – How to create an OLTP Data Model for US Mortgage URLA 1003 Application Form?

18 – Dimensional Data Modeling:


  • What is Business Intelligence?
  • What is Data Warehouse?
  • What is Data Mart?
  • What is ETL Process?
  • Difference between OLTP and Dimensional
  • What is Inman’s Approach?
  • What is Kimball’s Approach?
  • What is Dependent Data Mart? And What is an Independent Data Mart?
  • What is Source Schema and What is Target Schema?
  • How to design the Data Mart?
  • What is Star Schema?
  • What is Snowflake Schema?
  • What is Business Process?
  • What is a grain statement and what is the lowest level of Granularity?
  • What is a Dimension?
  • What is a Degenerate Dimension?
  • What is a Causal Dimension?
  • What is Junk Dimension?
  • What is Outrigger Dimension?
  • What is Slowly Changing Dimension Type1, Type2, and Type3?
  • What is a Fact or a Measure?
  • What is Additive Fact, Semi Additive fact and Non-Additive Fact?
  • What is a Fact Table?
  • What is Fact less Fact Table?
  • What is Transaction Fact?
  • What is Aggregate Fact?
  • What is Accumulation Fact?
  • What is a Periodic Fact?
  • What is a surrogate key?
  • What is the specialty of Date Key as a surrogate column?
  • How to avoid NULL VALUES in the primary keys of a Fact Table?

19 – Dimensional Data Models – Case Study:

  • Point of Sales Data Model – How to design the star schema?
  • US Mortgage URLA 1003 Data Model
  • Retail Bank Data Model– How to store ATM Transactions?
  • OLA/Uber Data Model – How to store ride information?
  • Cloud Data Model – How to store products sold on cloud environment
  • Banking Data Model: How to store Daily and Monthly Data?

20 – Fundamentals:

  • How to use Erwin Data Modeling Tool, Oracle SQL Data Modeler, TOAD Data Modeler, SAP Power Designer.

Online NoSQL Data Modeling Training

Course Details:

Course Syllabus:

  • What is nosql.
  • About MongoDB
  • CRUD – create, insert, delete, update operations
  • JSON
  • Three Data Model samples in MongoDB
  • Introduction to Hadoop Hotonworks Big Data environment
  • How MongoDB is used in Big Data environment – Example
  • Compare RDBMS Data Model with MongoDB Data Model
  • Compare important CRUD statements with RDBMS and MongoDB

SQL Server – Online training course, Classes, Practical sessions

SQL Server’s T-SQL Training with Agile and Data Modeling

Online Training Start Date : 9th January, 2023

Course Start Date: Training will be provided as per your convenient time slots! Please call us at 91-9080157239 for more details!


Chapter 1: Introduction about Data, Column, Datatype, Record, PK, FK

  • How to install SQL Server Management Studio?
  • How to install SQL Server Express Edition?
  • What is a database?
  • How to Backup / Delete / Recover a SQL Server Database?
  • How to Export / Import Data from SQL server?
  • How to Detach / Attach a Database?
  • What is Server Login / Database User / Schema / Role / Privileges?
  • What is Data?
  • What is a column?
  • What is a datatype?
  • What is a record?
  • What is a table?
  • What is primary key?
  • What is composite primary key?
  • What is a foreign key?
  • What is composite foreign key?
  • What is a schema?

Chapter 2: Introduction to SDLC, Waterfall Methodology, Agile Methodology

  • Introduction to Software Development Life Cycle.
  • What is Waterfall methodology?
  • What is Agile methodology?
    • Scrum Model
    • What is Product Catalog?
    • What is Sprint Catalog?
    • What is Project Team?
    • Who is Product Owner?
    • Scrum Development Team
    • Scrum Master
    • What is Sprint Planning?
    • What is Daily Scrum?
    • What is Sprint Review?
    • What is Sprint Retrospective?
    • What is Product Backlog Refinement?

Chapter 3: Introduction to Database and Application:

  • What is a Server?
  • Introduction to SQL Databases
  • What is a Client?
  • What is an Application?
  • What is a Desktop Application?
  • What is a Browser Based Application?
  • What is a Mobile Based Application?
  • What is Client Server Architecture?

Chapter 4: Data Analysis:

  • Introduction to Data Analysis from RDBMS perspective
  • Introduction to Data Profiling from RDBMS perspective

Chapter 5: Introduction to SQL Server Environment:

  • Basic Features, Components and Tools
  • How to start and stop SQL Server Instances and Services
  • Introduction to Management Studio
  • Types of System Databases in SQL
  • How to create a database?

Chapter 6: Data Definition Language (DDL):


  • What is a datatype?
  • Different types of datatypes


  • How to Create / Alter / Drop Table (column, datatype)
  • How to truncate a Table?


  • How to Create / DROP NULL and NOT NULL?
  • How to Create / Drop Primary Keys and Composite Primary Keys?
  • How to Create / Drop Foreign key Constraints?
  • How to Create / Drop Unique Constraint and Composite Unique Constraint?
  • How to Create / Drop Check Constraints?

Chapter 7: Data Manipulation Language (DML):

  • How to insert, delete and update date in a table?

Chapter 8: Data Query Language (DQL):

  • What is ANSI SQL?
  • What is T-SQL?

How Select Statements are used in OLTP and OLAP environment:

  • How to frame a Select Statement on all columns?
  • How to frame a Select Statement on few columns?
  • What is WHERE clause? How to select all records and few records?
  • How to use different conditions in where clause?
  • How to sort and unsort the data?
  • How to use Boolean operators in where clause?
  • How to use Arithmetic operators in where clause?
  • How to use IN operator in where clause?
  • How to use comparison operator in where clause?
  • How to use NULL and NOT NULL in the where clause?
  • How to use predefined (default) functions?
  • How to use set operators like UNIION and Intersect?
  • How to use Mathematical Functions?
  • How to use Character Functions?
  • How to use Advanced Functions?
  • How to use Date Functions?

Group Functions:

  • What is Grouping the data? And where it will be useful?
  • How to use group function MIN, MAX, SUM, AVG, COUNT
  • What is HAVING clause?
  • How to combine GROUP by and HAVING?


  • What is a Sub Query?
  • What is a Nested Query?
  • What is Inner Query?
  • What is Outer Query?
  • What is co-related Sub Query?


  • Inner Join or Simple Join
  • Right Outer Join
  • Left Outer Join
  • Full Outer Join

Chapter 9: NOSQL Databases:

  • Introduction to NoSQL Databases

Chapter 10: Normalization and E/R Diagram through Oracle’s SQL Developer Data Modeler:

  • What is Normalization?
  • What is Denormalization?
  • How to analyze the requirement?
  • How to find out entities and relationships through Normalization Techniques (1NF, 2NF, 3NF)?
  • How to draw E-R (Entity Relationship Diagram)? – One to One, One to many, Many to Many, Self-Referential Integrity (Recursive), Cardinality and Optionality.

Chapter 11: About Data Model:

  • Explanation of a Logical Data Model
  • Explanation of a Physical Data Model
  • How ER data (Normalized Data) is converted into Tables?
  • Explanation of Dimensional Data Model
  • What is OLTP environment?
  • What is OLAP environment?

Chapter 12: Duties and Responsibilities of a SQL Developer:

  • What is Role?
  • What is Level?
  • What is a duty?
  • What is a responsibility?
  • What are the duties and responsibilities of a SQL Developer?

Chapter 13: Introduction to Big Data:

  • HDFS
  • MapReduce
  • Hadoop
  • Hive
  • Pig Script
  • Yarn
  • ZooKeeper
  • Tez
  • Spark
  • Storm
  • MongoDB
  • HBase
  • MySQL
  • Cassandra

What is Entity Relationship Diagram (ER Diagram) or ERD?

Entity Relationship Diagram (also called as ER Diagram, ER Model, ERD) contains entities/attributes and relationships with those entities. ER Model is a methodological approach to create entities in normalized forms to minimise redundancy. It is drawn with the use of Data Modeling Tools and the following steps are done to create the entity relationship diagram.

  1. Understanding the business requirements
  2. Meetings / discussions with stakeholders (BA/SME/PM etc) to find out entities and relationships
  3. Data Modeler designs the ER diagram.

Data Modeling with ER Model:

In the above mentioned example,

1. Following entities are created by data modeler

  1. Department
  2. Gender
  3. Employee
  4. Salary Grade
  5. Degree

2. Then the data modeler adds the relevant attributes to those entities.

3. Creating attributes: Example Employee

  1. Employee ID
  2. Department Number
  3. Salary Grade Identifier
  4. Gender Code
  5. Degree Code
  6. Employee Name
  7. Birth DATE

4. The data modeler assigns relevant datatypes for each attribute based on the type of data stored:

Example Employee ID in employee entity

5. Relationships:

  1. After creating entities and attributes the data modeler decides how to create the primary key, foreign key
  2. Creating primary key:
    1. Example: Employee ID in Employee entity
  3. Creating foreign key:
    1. Example: Employee entity references Department entity, Gender entity, Salary Grade and Degree Entity

Optionality and Cardinality  options:


Creating foreign key:

  1. Example: Employee entity references Department entity, Gender entity, Salary Grade and Degree Entity

In The below ER diagram created from Erwin Data Modeling Tool by using Information Engineering (IE) notation, near to that department entity, one can see ZERO and ONE and near employee entity, ZERO AND ONE AND MORE. These symbols have specific meaning and the data modeler has assigned the right symbols due to business rules.

Similarly, entities are created in ER diagram and the data modeler gets the approval from the business team, technical to release the data models.

Data Modeling Software Tools Trial Versions:

Oracle has released “SQL Developer Data Modeler” and it is a free data modeling tool. If you want to become a data modeler, you can start designing data with “SQL Developer Data Modeler”.

Download ‘SQL Developer Data Modeler’:

With Erwin and PowerDesigner, you can get the trial version.

Download Erwin:

Download PowerDesigner:


If you are interested to learn data modeling by using Erwin or SAP PowerDesigner or Oracle SQL Data Modeler, please reach us for more details – or 91-90801 57239.

Business Process Topics – Index

Business Process & Business Modeling:

Data Modeling Topics – Index

Data Modeling

Data Modeling Overview

Data Modeling Tools

Creating Objects & Data Modeling Relationships

Data Modeling Types


Physical Data Modeling

Modeling Data Warehouse and Data Mart

Interview Questions

Data Modeling Training with SAP PowerDesigner

Logical Data Modeling Training with SAP PowerDesigner 16.5:

  • How to normalize the logical data model?
  • Clinic, Students, Order Form Model Examples
  • How to group entities?
  • How to add data item, entity attributes to entities?
  • How to add identifier? (Key group in Erwin)
  • How to add inheritance link? (subtype relationship in Erwin)
  • How to add inheritance? (subtype category in Erwin)
  • How to create relationships?
  • What is cardinality? How to connect different entities with relationship lines?
  • How to add diagram?  (stored display and subject area in Erwin)
  • How to add annotations? (notes in Erwin)
  • How to add text block (text symbol in Erwin)
  • How to add text symbol? (text block in Erwin)
  • How to compare different versions of a Logical Data Model?
  • Banking, Mortgage, Staffing, Insurance, and Training Data Models

Physical Data Modeling Training with SAP PowerDesigner 16.5:

  • Understanding the technical requirements/specifications from Database Administrator.
  • How to add those requirements/specifications in a physical data model?
  • How to add check constraints?
  • How to add Reference (Relationship in Erwin)?
  • How to convert logical data model to physical data model?
  • How to implement the physical data model in different database (forward engineering?
  • What is reverse engineering?
  • How to compare the different versions of a physical data model?
  • How to compare the physical data model and a Current DBMS (Current DBMS)?
  • Banking, Mortgage, Staffing, Insurance, and Training Data Model Examples
  • Comparison between Erwin and PowerDesigner

Dimensional Data Modeling training with SAP PowerDesigner 16.5?


  • Why do you need a data warehouse in SAP PowerDesigner Data Modeling?
  • What is the reason for a data mart?
  • Why is star schema? How is that different from dimensional data modeling?
  • Why customers prefer dimensional data modeling or snow flake modeling?
  • What are slowly changing dimensions?
  • Point of Sales Data Model, Banking, Mortgage, and Clinic Examples

If you need more information on this SAP PowerDesigner Data Modeling Training, please contact: or 91-9080157239.

Online Training Course Start Date: 9th January, 2023.

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