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:

(Source: www.Erwin.com)

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’:

https://www.oracle.com/database/technologies/appdev/datamodeler.html.

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

Download Erwin:

http://go.erwin.com/erwin-data-modeler-free-trial

Download PowerDesigner:

https://www.sap.com/cmp/syb/crm-xm16-gam-it-dtcpdt/index.html

 

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 – Training@learndatamodeling.com 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


Comparison


Physical Data Modeling


Modeling Data Warehouse and Data Mart


Interview Questions


Advanced 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: Training@LearnDataModeling.com or 91-9080157239.

Data Modeling Demo Videos

01. Data Modeling Development Life Cycle

 

02. Data Warehouse Training – Table and PK

 

03. Simple Select Statement and Alter Statements

 

04. Data Warehouse Training ETL Tools

 

05. Demo Data Modeling and Data Warehouse Training Normalization

 

06 Demo Data Modeling and Data Warehouse Training – Cardinality and Optionality

 

 

Oracle Database DDL Statements – DROP Object Commands

Oracle Database Data Definition Language (DDL Statements) – DROP Object Commands:

In this section, we will try to explain about important database DROP commands that are used by a data modeler by relating it with our example data.

Drop Index:

DROP INDEX IND_SSN; 

Drop Synonym:

DROP SYNONYM SYN_EMPLOYEE_DTL; 

Drop View:

DROP VIEW VIEW_EMPLOYEE_DTL; 

Drop Sequence:

DROP SEQUENCE SEQ_EMPLOYEE_DTL; 

Drop Trigger:

DROP TRIGGER TRG_SEQ_EMPLOYEE_DTL; 

Drop Table:

DROP TABLE EMPLOYEE_DTL; 

Drop Table with Cascading Option:

In our example tables, try to drop tables GENDER_LKP, and DEPARTMENT_LKP after the data is loaded into GENDER_LKP, DEPARTMENT_LKP, and EMPLOYEE_DTL. You will get an error message.

If you want to drop parent tables that are connected with child tables, then you can use the following command.

DROP TABLE GENDER_LKP CASCADE CONSTRAINTS;

DROP TABLE DEPARTMENT_LKP CASCADE CONSTRAINTS; 

 

Oracle Database DML Commands

Oracle Database Data Manipulation Language (DML) Commands:

In this section, we will try to explain about important database DML commands that are used by a data modeler.

Insert statements:

  • Insert Values into GENDER_LKP:

Insert statements are used to insert data into the table. In our example, we have used SYSDATE, an Oracle’s function, which is used to insert the date and time into the column “DTTM_STMP”.

INSERT INTO GENDER_LKP VALUES ( ‘M’, ‘MALE’, SYSDATE);

INSERT INTO GENDER_LKP VALUES (‘F’, ‘FEMALE’, SYSDATE); 

  • Insert Values into DEPARTMENT_LKP:
INSERT INTO DEPARTMENT_LKP VALUES (10, ‘IT’, SYSDATE);

INSERT INTO DEPARTMENT_LKP VALUES (20, ‘HR’, SYSDATE); 

  • Insert Values into EMPLOYEE_DTL:
INSERT INTO EMPLOYEE_DTL(GNDR_CD, DPTMT_NUM, FRST_NM, LST_NM, MDLE_NM, BRTH_DT, SSN, SLRY_AMT, DTTM_STMP) VALUES (‘M’, 10,’Kevin’,’A’,’Schulte’, TO_DATE(’13-OCT-1969′,’DD-MON-YYYY’),’123-45-67′, 5000,SYSDATE);

 

INSERT INTO EMPLOYEE_DTL(GNDR_CD, DPTMT_NUM, FRST_NM, LST_NM, MDLE_NM, BRTH_DT, SSN, SLRY_AMT, DTTM_STMP) VALUES (‘F’, NULL,’Valencia’,’D’,’Schipper’, TO_DATE(’20-APR-1973′,’DD-MON-YYYY’),’765-43-21′, 5000,SYSDATE);

 

INSERT INTO EMPLOYEE_DTL(GNDR_CD, DPTMT_NUM, FRST_NM, LST_NM, MDLE_NM, BRTH_DT, SSN, SLRY_AMT, DTTM_STMP) VALUES (‘M’, 10,’Chris’,’A’,’HERIER’, TO_DATE(’10-JUN-1963′,’DD-MON-YYYY’),’795-82-63′, 6000,SYSDATE); 

  • Insert Values into EMPLOYEE_DTL_COPY:

This statement will copy all records from table “EMPLOYEE_DTL” to “EMPLOYEE_DTL_COPY”.

INSERT INTO EMPLOYEE_DTL_COPY SELECT * FROM EMPLOYEE_DTL; 

Update Statements:

Update statements are used to update records with/without conditions. The following example uses a condition in where clause. Update statements can be committed to the database by using explicit “commit” command or it can be rolled back by using “rollback” command.

UPDATE EMPLOYEE_DTL SET DPTMT_NUM=20 WHERE EMP_DTL_ID=2; 

Delete Statements:

Delete statements are used to delete records with/without conditions. The following example uses some condition in where clause. Delete statements can be committed to the database by using explicit “commit” command or it can be rolled back by using “rollback” command.

DELETE FROM EMPLOYEE_DTL WHERE EMP_DTL_ID=2; 

Select all rows:

Select statements are used to retrieve records from the database with/without conditions. Select statements are the most powerful commands, which you have to learn since you can avoid unnecessary “PLSQL” in many cases.

SELECT * FROM EMPLOYEE_DTL; 

Select rows by using a WHERE clause:

SELECT * FROM EMPLOYEE_DTL WHERE EMP_DTL_ID=1; 

Select few columns:

SELECT EMP_DTL_ID, FRST_NM, SLRY_AMT FROM EMPLOYEE_DTL WHERE

SSN=’123-45-67′; 

Select records by Sorting (ASC = ascending and DESC = descending):

SELECT * FROM EMPLOYEE_DTL ORDER BY EMP_DTL_ID ASC;

SELECT * FROM EMPLOYEE_DTL ORDER BY EMP_DTL_ID DESC; 

Select records by Grouping and Having clause:

SELECT DPTMT_NUM, COUNT(DPTMT_NUM) FROM EMPLOYEE_DTL GROUP BY DPTMT_NUM;

 

SELECT DPTMT_NUM, COUNT(DPTMT_NUM) FROM EMPLOYEE_DTL GROUP BY DPTMT_NUM HAVING COUNT(DPTMT_NUM) > 1;

 

SELECT DPTMT_NUM, COUNT(DPTMT_NUM) FROM EMPLOYEE_DTL GROUP BY DPTMT_NUM HAVING COUNT(DPTMT_NUM) < 2; 

Select records by using a Sub Query:

SELECT * from EMPLOYEE_DTL WHERE DPTMT_NUM IN(SELECT DPTMT_NUM FROM DEPARTMENT_LKP WHERE DPTMT_DESC=’IT’); 

Select Distinct records:

SELECT DISTINCT(DPTMT_NUM) FROM EMPLOYEE_DTL; 

Select Count of records:

SELECT COUNT(*) FROM EMPLOYEE_DTL; 

 

Oracle Database DDL Statements – ALTER Commands

Oracle Database Data Definition Language (DDL Statements) – ALTER Commands:

In this section, we will try to explain about important database ALTER commands that are used by a data modeler by relating it with our example data.

ALTER TABLE – Add Column:

 ALTER TABLE EMPLOYEE_DTL ADD JOIN_DATE DATE; 

ALTER TABLE – Rename Column:

 ALTER TABLE EMPLOYEE_DTL RENAME column JOIN_DATE TO EMP_JOIN_DT; 

ALTER TABLE – Modify column’s Data Type:

 ALTER TABLE EMPLOYEE_DTL MODIFY EMP_JOIN_DT VARCHAR2(10); 

ALTER TABLE – Drop Column:

 ALTER TABLE EMPLOYEE_DTL DROP COLUMN EMP_JOIN_DT; 

ALTER TABLE – Add Check Constraint:

ALTER TABLE EMPLOYEE_DTL ADD CONSTRAINT CH_SAL CHECK(SLRY_AMT BETWEEN 4000 AND 7000); 

ALTER TABLE – Add Unique Constraint:

ALTER TABLE EMPLOYEE_DTL ADD CONSTRAINT UN_SSN UNIQUE(SSN); 

ALTER TABLE – Disable/Enable/Drop Constraint:

ALTER TABLE EMPLOYEE_DTL DISABLE CONSTRAINT UN_SSN; 

ALTER TABLE EMPLOYEE_DTL ENABLE CONSTRAINT UN_SSN;

ALTER TABLE EMPLOYEE_DTL DROP CONSTRAINT UN_SSN; 

ALTER TABLE – Modify Constraint:

 ALTER TABLE EMPLOYEE_DTL MODIFY SLRY_AMT NUMBER(7,2) NULL;

 ALTER TABLE EMPLOYEE_DTL MODIFY SLRY_AMT NUMBER(7,2) NOT NULL; 

Challenging Situations in Data Modeling

Challenges & Solutions in Data Modeling:

Anyone can Learn Data Modeling Concepts by reading some books or going through online or by getting some help from experts in the field. But practically, while working with a particular Data Model, there may arise many challenging situations where one has to think about various possibilities and requirements, before imposing a cardinality rule or before creating a relationship. Will it be sufficient if I go with one additional entity or I should create one lookup in order to satisfy the Business Requirement? Will the current data structures be hold good for any future expansions and modifications?

So many challenging situations may arise during the course of one Data Modeling Life Cycle. This page is entirely for that purpose which makes Data Modeler to be to think ahead and decide on what rule to apply in order to create the right Data Model.

We will come up with many difficult situations and present you with some practical based scenarios and post it on this page on the daily or weekly basis. Data Modelers make a note of this page and use it as a reference or an assignment to improve your skills in the Data Modeling Field.

Challenging Situations in Data Modeling from the Client End:
  • No documents or fewer documents with less information which explains the business process and business rules.
  • Less knowledge and no proper explanation from SME or BAs.
  • User requirements and demands are more.
  • No proper plan in the Enterprise Architecture.
Challenging Situations in Data Modeling from the Data Modeler’s Perspective:
  • Not able to understand the business requirements.
  • Understanding the business requirements but not able to predict the entities required for this project.
  • Understanding the entities required but not able to place the attributes properly in the entity.
  • Placing the attributes in entities but not able to create identifying relationships or non-identifying relationships.
  • Able to create identifying and non-identifying relationships but not sure whether ZeroOrOne to ZeroOneorMore, One to ZeroOneorMore.

How the change in the business rules affects the data model?

Original Business Rule 1:

  • Employee’s present manager to whom he reports must be tracked.
  • An entity called Employee is created and by using Self Referential Integrity and the role name, Manager is added.

Business Rule 1 Change:

  • Employee’s previous manager, present manager and future managers are to be tracked.

Original Business Rule 2:

  • Employees current residential address must be tracked.
  • An entity called address is created and you connect that address with employee entity.

Business Rule 2 Change:

Employees previous/current/future residential address must be tracked.

Here how these Business Rules(1 & 2) affects the current Data Model and as a data modeler, how will you implement these changes? What is the best way to do it?

Business Rule 3:

If there are three definite values for a column, and if you are sure that these values never change over time then what approach you will follow? – a Lookup or a Check Constraint?

Example: In URLA 1003 form provided by Fannie Mae, Page No.5, Section No. 4 one can see Purchase, Refinance and Other as the values for the field “Loan Purpose”. Should we create a lookup for these 3 values or will it be better if we create an identifier and impose a check constraint on these 3 values.

Business Rule 4:

How will you implement a Candidate Key – By creating it as a Primary Key or an Unique Constraint?

Example: Social Security Number is always a Candidate Key and whether this should be created as a Primary Key in a table or a stand alone column with Unique Constraint imposed on it.

 

Reach US!!!

 

  • We provide online training in advanced OLTP Data Modeling and DIMENSIONAL Data Modeling.
  • We also teach the data structures with Data Analytics Software “R”.
  • We provide online Data Modeling Project Support when you get struck with projects that you are involved.
  • We can analyse your Business Requirements, understand and suggest solutions to create OLTP Data Models and Dimensional Data models.
  • We provide Data Modeling Interview Preparation Sessions with a lot of Data Modeling Interview Questions/Answers, which will help you to clear any interview.

If you are interested, please reach us at Training@LearnDataModeling.com or 91-9080157239

Online Data Modeling Job Support for OLTP & Dimensional Data Modeling

CPT/OPT EAD/L2 EAD/H4 EAD holders:

If a new opportunity is provided and you are facing difficult challenges in understanding the business requirements to derive data models.

Data Modelers, Data Analyst,  ETL Developers and BI Developers:

Interview:

  • If you face tough scenario based  interview questions and not able to answer.

Less Productivity: 

  • If the duties and responsibilities are changed by the client for no reasons and if you are one among those who find it difficult to cope up with puzzling scenarios.

In Between Projects: 

  • If your roles and responsibilities must be updated in near future
  • If you are finding difficulties in data modeling (designing RDBMS database or Data Warehouse or Data Mart),  you want to take your knowledge and understanding of the Database design to the next level.

If you are the one who got struck in the above-mentioned scenarios or if you are finding difficulties in data modeling (designing RDBMS database or Data Warehouse or Data Mart), please approach Training@LearnDataModeling.com or 91-90801 57239.

What we can offer through ONLINE:

  • Our consultants have more than 15 plus years of experience in Data Modeling in normalized databases, Data Warehouses and Data Marts.
  • Has hands on with OLTP / Dimensional Data Modeling, OLAP Cubes, Informatica, Oracle Warehouse Builder, Cognos, Brio and SQL/PLSQL.
  • Provide solutions on data modeling.
  • Provide solutions on data analysis, business analysis, user expectations related to data modeling.
  • Share knowledge to implement complicated Data Modeling scenarios.
  • Will meet your deadlines on each individual task or group of tasks.
  • Can sign agreement on a daily basis/weekly basis/monthly basis.

 

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