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 12.1.0.2.0

  • Insert, Update, Delete Statement
  • Select Statements
  • NULL, NOT NULL
  • 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

Keys:

  • “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

OLTP:

  • 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:

Concepts:

  • 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:

  • Start Date: 7th September 2019
  • Days: Saturday and Sunday 
  • Duration : 6 hours to 10 hours
  • Session duration: 1.5 hours per day 
  • Training Fees: 100 dollars for course and 25 dollars for videos
  • Time: 6.00 P.M to 7.30 P.M Indian Standard Time

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

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

Email: AntonysTrainingandSolution@gmail.com

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):

Datatype:

  • What is a datatype?
  • Different types of datatypes

Table:

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

Constraint:

  • 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?

Queries:

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

Joins:

  • 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:

(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

In this section, you can view some of the Demo Videos that I have posted on the YouTube. You can find the Syllabus of the actual Data Modeling Video Tutorials here! If you are interested in buying this Video, please reach us at 91-9080157239 or you email us your requirements to AntonysTrainingandSolution@gmail.com.

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; 

 

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