Building a Comprehensive Human Resources Management System

Introduction

In today’s rapidly evolving corporate environment, managing human resources efficiently is more critical than ever. An effective Human Resources Management System (HRMS) can streamline employee management processes, improve productivity, and offer valuable insights for decision-making. With the power of Oracle databases, we can build a sophisticated HRMS that handles employee records, manages payroll, and facilitates in-depth data analysis with ease.

This blog will walk you through a comprehensive HRMS designed using Oracle, complete with table structures, relationship setups, and essential SQL queries for extracting valuable HR insights.

Database Design Overview

The HRMS is structured around seven main tables. There are-

Employees Table: Stores basic employee information, including names, job roles, salary, department, and manager details.
Departments Table: Keeps track of all departments within the organization, along with their respective locations and managers.
Regions Table: Defines various geographical regions (e.g., Europe, Americas, Asia).
Jobs Table: Contains job titles along with the minimum and maximum salary ranges.
Countries Table: Contains country names and their respective regions.
Job_history Table: Maintains a historical record of employee movements and job changes within the organization.
Locations Table: Stores detailed location data for each department.

This relational database schema enables efficient storage and management of employee data, including their job roles, departments, salary details, and job history across different regions. Each table is connected through primary and foreign key relationships, ensuring data integrity and minimizing redundancy.

Model View:

Queries:

First, we will set up our database, then we will execute some SQL queries to extract meaningful insights. Here are some SQL queries-

Retrieve all employees in a specific department.
Calculate the average salary in each department.
List employees who were hired in the year of 1999.
Write a query to find employees who have never worked in the “Sales” department throughout their job history.
Calculate the average salary for each region and compare it with the average salary within each department of that region.
Determine how many employees are located in each country and list the top 3 countries with the highest number of employees working in the “IT” job category.
Find employees with the longest tenure in the company and list each of their job titles along with the duration they held each job.
Analyze how the number of employees in each department has changed over the years. Visualize which departments have grown or shrunk significantly.
Compare the highest and lowest paid employees across different locations. Determine if there’s a noticeable salary variation between different locations in the same country.
Analyze hiring trends to determine which months consistently see the highest number of new hires. Consider if this trend changes across different departments.
Write a report on the distribution of employees across regions for a specific job category, and discuss any notable patterns in diversity.

Step 1: Creating the Database Tables & Inserting Data into Tables

The initial step involves creating the database tables using SQL commands.

Creating Employee’s table

Here is a SQL snippet for creating the Employee’s table:

SQL

CREATE TABLE employees (
    employee_id int PRIMARY KEY,
    first_name VARCHAR(20),
    last_name VARCHAR(25) NOT NULL,
    email VARCHAR(25) NOT NULL,
    phone_number VARCHAR(20),
    hire_date DATE,
    job_id VARCHAR(10),
    salary money,
    commission_pct int NULL,
    manager_id int,
    department_id int
);

Insert data into the Employee’s table:

SQL

INSERT INTO employees VALUES ( 100, 'Steven', 'King', 'SKING', '515.123.4567', '17-JUN-1987', 'AD_PRES', 24000, NULL, NULL, 90);
INSERT INTO employees VALUES ( 101, 'Neena', 'Kochhar', 'NKOCHHAR', '515.123.4568', '21-SEP-1989', 'AD_VP', 17000, NULL, 100, 90);
INSERT INTO employees VALUES ( 102, 'Lex', 'De Haan', 'LDEHAAN', '515.123.4569', '13-JAN-1993', 'AD_VP', 17000, NULL, 100, 90);
INSERT INTO employees VALUES ( 103, 'Alexander', 'Hunold', 'AHUNOLD', '590.423.4567', '03-JAN-1990', 'IT_PROG', 9000, NULL, 102, 60);
INSERT INTO employees VALUES ( 104, 'Bruce', 'Ernst', 'BERNST', '590.423.4568','21-MAY-1991', 'IT_PROG', 6000, NULL, 103, 60);
INSERT INTO employees VALUES ( 105, 'David', 'Austin', 'DAUSTIN', '590.423.4569', '25-JUN-1997', 'IT_PROG', 4800, NULL, 103, 60);
INSERT INTO employees VALUES ( 106, 'Valli', 'Pataballa', 'VPATABAL', '590.423.4560','05-FEB-1998', 'IT_PROG', 4800, NULL, 103, 60);
INSERT INTO employees VALUES ( 107, 'Diana', 'Lorentz', 'DLORENTZ', '590.423.5567', '07-FEB-1999', 'IT_PROG', 4200, NULL, 103, 60);
INSERT INTO employees VALUES ( 108, 'Nancy', 'Greenberg', 'NGREENBE', '515.124.4569', '17-AUG-1994', 'FI_MGR', 12000, NULL, 101, 100);
INSERT INTO employees VALUES ( 109, 'Daniel', 'Faviet', 'DFAVIET', '515.124.4169', '16-AUG-1994', 'FI_ACCOUNT', 9000, NULL, 108, 100);
INSERT INTO employees VALUES ( 110, 'John', 'Chen', 'JCHEN', '515.124.4269', '28-SEP-1997', 'FI_ACCOUNT', 8200, NULL, 108, 100);
INSERT INTO employees VALUES ( 111, 'Ismael', 'Sciarra', 'ISCIARRA', '515.124.4369', '30-SEP-1997', 'FI_ACCOUNT', 7700, NULL, 108, 100);
INSERT INTO employees VALUES ( 112, 'Jose Manuel', 'Urman', 'JMURMAN', '515.124.4469', '07-MAR-1998', 'FI_ACCOUNT', 7800, NULL, 108, 100);
INSERT INTO employees VALUES ( 113, 'Luis', 'Popp', 'LPOPP', '515.124.4567', '07-DEC-1999', 'FI_ACCOUNT', 6900, NULL, 108, 100);
INSERT INTO employees VALUES ( 114, 'Den', 'Raphaely', 'DRAPHEAL', '515.127.4561', '07-DEC-1994', 'PU_MAN', 11000, NULL, 100, 30);
INSERT INTO employees VALUES ( 115, 'Alexander', 'Khoo', 'AKHOO', '515.127.4562', '18-MAY-1995', 'PU_CLERK', 3100, NULL, 114, 30);
INSERT INTO employees VALUES ( 116, 'Shelli', 'Baida', 'SBAIDA', '515.127.4563', '24-DEC-1997', 'PU_CLERK', 2900, NULL, 114, 30);
INSERT INTO employees VALUES ( 117, 'Sigal', 'Tobias', 'STOBIAS', '515.127.4564', '24-JUL-1997', 'PU_CLERK', 2800, NULL, 114, 30);
INSERT INTO employees VALUES ( 118, 'Guy', 'Himuro', 'GHIMURO', '515.127.4565', '15-NOV-1998', 'PU_CLERK', 2600, NULL, 114, 30);
INSERT INTO employees VALUES ( 119, 'Karen', 'Colmenares', 'KCOLMENA', '515.127.4566', '10-AUG-1999', 'PU_CLERK', 2500, NULL, 114, 30);
INSERT INTO employees VALUES ( 120, 'Matthew', 'Weiss', 'MWEISS', '650.123.1234', '18-JUL-1996', 'ST_MAN', 8000, NULL, 100, 50);
INSERT INTO employees VALUES ( 121, 'Adam', 'Fripp', 'AFRIPP', '650.123.2234', '10-APR-1997', 'ST_MAN', 8200 , NULL, 100, 50);
INSERT INTO employees VALUES ( 122, 'Payam', 'Kaufling', 'PKAUFLIN', '650.123.3234', '01-MAY-1995', 'ST_MAN', 7900, NULL, 100, 50);
INSERT INTO employees VALUES ( 123, 'Shanta', 'Vollman', 'SVOLLMAN', '650.123.4234' , '10-OCT-1997', 'ST_MAN', 6500, NULL, 100, 50);
INSERT INTO employees VALUES ( 124, 'Kevin', 'Mourgos', 'KMOURGOS', '650.123.5234', '16-NOV-1999', 'ST_MAN', 5800, NULL, 100, 50);
INSERT INTO employees VALUES ( 125, 'Julia', 'Nayer', 'JNAYER', '650.124.1214', '16-JUL-1997', 'ST_CLERK', 3200, NULL, 120, 50);
INSERT INTO employees VALUES ( 126, 'Irene', 'Mikkilineni', 'IMIKKILI', '650.124.1224', '28-SEP-1998', 'ST_CLERK', 2700, NULL, 120, 50);
INSERT INTO employees VALUES ( 127, 'James', 'Landry', 'JLANDRY', '650.124.1334', '14-JAN-1999', 'ST_CLERK', 2400, NULL, 120, 50);
INSERT INTO employees VALUES ( 128, 'Steven', 'Markle', 'SMARKLE', '650.124.1434', '08-MAR-2000', 'ST_CLERK', 2200, NULL, 120, 50);
INSERT INTO employees VALUES ( 129, 'Laura', 'Bissot', 'LBISSOT', '650.124.5234', '20-AUG-1997', 'ST_CLERK', 3300, NULL, 121, 50);
INSERT INTO employees VALUES ( 130, 'Mozhe', 'Atkinson', 'MATKINSO', '650.124.6234', '30-OCT-1997', 'ST_CLERK', 2800, NULL, 121, 50);
INSERT INTO employees VALUES ( 131, 'James', 'Marlow', 'JAMRLOW', '650.124.7234', '16-FEB-1997','ST_CLERK', 2500, NULL, 121, 50);
INSERT INTO employees VALUES ( 132, 'TJ', 'Olson', 'TJOLSON', '650.124.8234', '10-APR-1999','ST_CLERK', 2100, NULL, 121, 50);
INSERT INTO employees VALUES ( 133, 'Jason', 'Mallin', 'JMALLIN', '650.127.1934', '14-JUN-1996', 'ST_CLERK', 3300, NULL, 122, 50);
INSERT INTO employees VALUES ( 134, 'Michael', 'Rogers', 'MROGERS', '650.127.1834', '26-AUG-1998', 'ST_CLERK', 2900, NULL, 122, 50);
INSERT INTO employees VALUES ( 135, 'Ki', 'Gee', 'KGEE', '650.127.1734', '12-DEC-1999', 'ST_CLERK', 2400, NULL, 122, 50);
INSERT INTO employees VALUES ( 136, 'Hazel', 'Philtanker', 'HPHILTAN', '650.127.1634', '06-FEB-2000', 'ST_CLERK', 2200, NULL, 122, 50);
INSERT INTO employees VALUES ( 137, 'Renske', 'Ladwig', 'RLADWIG', '650.121.1234', '14-JUL-1995', 'ST_CLERK', 3600, NULL, 123, 50);
INSERT INTO employees VALUES ( 138, 'Stephen', 'Stiles', 'SSTILES', '650.121.2034', '26-OCT-1997', 'ST_CLERK' , 3200, NULL, 123, 50);
INSERT INTO employees VALUES ( 139, 'John', 'Seo', 'JSEO', '650.121.2019', '12-FEB-1998', 'ST_CLERK', 2700, NULL, 123, 50);
INSERT INTO employees VALUES ( 140, 'Joshua', 'Patel', 'JPATEL', '650.121.1834', '06-APR-1998', 'ST_CLERK', 2500, NULL, 123, 50);
INSERT INTO employees VALUES ( 141, 'Trenna', 'Rajs' , 'TRAJS' , '650.121.8009', '17-OCT-1995', 'ST_CLERK', 3500, NULL, 124, 50);
INSERT INTO employees VALUES ( 142, 'Curtis', 'Davies', 'CDAVIES', '650.121.2994', '29-JAN-1997', 'ST_CLERK', 3100, NULL, 124, 50);
INSERT INTO employees VALUES ( 143, 'Randall', 'Matos', 'RMATOS', '650.121.2874','15-MAR-1998', 'ST_CLERK', 2600, NULL, 124, 50);
INSERT INTO employees VALUES ( 144, 'Peter', 'Vargas', 'PVARGAS', '650.121.2004', '09-JUL-1998', 'ST_CLERK', 2500, NULL, 124, 50);
INSERT INTO employees VALUES ( 145, 'John', 'Russell', 'JRUSSEL', '011.44.1344.429268', '01-OCT-1996', 'SA_MAN', 14000, .4, 100, 80);
INSERT INTO employees VALUES ( 146, 'Karen', 'Partners', 'KPARTNER' , '011.44.1344.467268', '05-JAN-1997', 'SA_MAN', 13500, .3, 100, 80);
INSERT INTO employees VALUES ( 147, 'Alberto', 'Errazuriz', 'AERRAZUR', '011.44.1344.429278', '10-MAR-1997', 'SA_MAN', 12000, .3, 100, 80);
INSERT INTO employees VALUES ( 148, 'Gerald', 'Cambrault', 'GCAMBRAU', '011.44.1344.619268', '15-OCT-1999', 'SA_MAN', 11000, .3, 100, 80);
INSERT INTO employees VALUES ( 149, 'Eleni', 'Zlotkey', 'EZLOTKEY', '011.44.1344.429018', '29-JAN-2000', 'SA_MAN', 10500, .2, 100, 80);
INSERT INTO employees VALUES ( 150, 'Peter', 'Tucker', 'PTUCKER', '011.44.1344.129268', '30-JAN-1997', 'SA_REP', 10000, .3, 145, 80);
INSERT INTO employees VALUES ( 151, 'David', 'Bernstein', 'DBERNSTE', '011.44.1344.345268', '24-MAR-1997', 'SA_REP', 9500, .25, 145, 80);
INSERT INTO employees VALUES ( 152, 'Peter', 'Hall', 'PHALL', '011.44.1344.478968', '20-AUG-1997', 'SA_REP', 9000, .25, 145, 80);
INSERT INTO employees VALUES ( 153, 'Christopher', 'Olsen', 'COLSEN', '011.44.1344.498718', '30-MAR-1998', 'SA_REP', 8000, .2, 145, 80);
INSERT INTO employees VALUES ( 154, 'Nanette', 'Cambrault', 'NCAMBRAU', '011.44.1344.987668', '09-DEC-1998', 'SA_REP', 7500, .2, 145, 80);
INSERT INTO employees VALUES ( 155, 'Oliver', 'Tuvault', 'OTUVAULT', '011.44.1344.486508', '23-NOV-1999', 'SA_REP', 7000, .15, 145, 80);
INSERT INTO employees VALUES ( 156, 'Janette', 'King', 'JKING', '011.44.1345.429268', '30-JAN-1996', 'SA_REP', 10000, .35, 146, 80);
INSERT INTO employees VALUES ( 157, 'Patrick', 'Sully', 'PSULLY', '011.44.1345.929268', '04-MAR-1996', 'SA_REP', 9500, .35, 146, 80);
INSERT INTO employees VALUES ( 158, 'Allan', 'McEwen', 'AMCEWEN', '011.44.1345.829268', '01-AUG-1996', 'SA_REP', 9000, .35, 146, 80);
INSERT INTO employees VALUES ( 159, 'Lindsey', 'Smith', 'LSMITH', '011.44.1345.729268', '10-MAR-1997', 'SA_REP', 8000, .3, 146, 80);
INSERT INTO employees VALUES ( 160, 'Louise', 'Doran', 'LDORAN', '011.44.1345.629268', '15-DEC-1997', 'SA_REP', 7500, .3, 146, 80);
INSERT INTO employees VALUES ( 161, 'Sarath', 'Sewall', 'SSEWALL', '011.44.1345.529268', '03-NOV-1998', 'SA_REP', 7000, .25, 146, 80);
INSERT INTO employees VALUES ( 162, 'Clara', 'Vishney', 'CVISHNEY', '011.44.1346.129268', '11-NOV-1997', 'SA_REP', 10500, .25, 147, 80);
INSERT INTO employees VALUES ( 163, 'Danielle', 'Greene', 'DGREENE', '011.44.1346.229268', '19-MAR-1999', 'SA_REP', 9500, .15, 147, 80);
INSERT INTO employees VALUES ( 164, 'Mattea', 'Marvins', 'MMARVINS', '011.44.1346.329268','24-JAN-2000', 'SA_REP', 7200, .10, 147, 80);
INSERT INTO employees VALUES ( 165, 'David', 'Lee', 'DLEE', '011.44.1346.529268', '23-FEB-2000', 'SA_REP', 6800, .1, 147, 80);
INSERT INTO employees VALUES ( 166, 'Sundar', 'Ande', 'SANDE', '011.44.1346.629268', '24-MAR-2000', 'SA_REP', 6400, .10, 147, 80);
INSERT INTO employees VALUES ( 167, 'Amit', 'Banda', 'ABANDA', '011.44.1346.729268', '21-APR-2000', 'SA_REP', 6200, .10, 147, 80);
INSERT INTO employees VALUES ( 168, 'Lisa', 'Ozer', 'LOZER', '011.44.1343.929268', '11-MAR-1997', 'SA_REP', 11500, .25, 148, 80);
INSERT INTO employees VALUES ( 169 , 'Harrison', 'Bloom', 'HBLOOM', '011.44.1343.829268', '23-MAR-1998', 'SA_REP', 10000, .20, 148, 80);
INSERT INTO employees VALUES ( 170, 'Tayler', 'Fox', 'TFOX', '011.44.1343.729268', '24-JAN-1998', 'SA_REP', 9600, .20, 148, 80);
INSERT INTO employees VALUES ( 171, 'William', 'Smith', 'WSMITH', '011.44.1343.629268', '23-FEB-1999', 'SA_REP', 7400, .15, 148, 80);
INSERT INTO employees VALUES ( 172, 'Elizabeth', 'Bates', 'EBATES', '011.44.1343.529268', '24-MAR-1999', 'SA_REP', 7300, .15, 148, 80);
INSERT INTO employees VALUES ( 173, 'Sundita', 'Kumar', 'SKUMAR', '011.44.1343.329268', '21-APR-2000', 'SA_REP', 6100, .10, 148, 80);
INSERT INTO employees VALUES ( 174, 'Ellen', 'Abel', 'EABEL', '011.44.1644.429267', '11-MAY-1996', 'SA_REP', 11000, .30, 149, 80);
INSERT INTO employees VALUES ( 175, 'Alyssa', 'Hutton', 'AHUTTON', '011.44.1644.429266', '19-MAR-1997', 'SA_REP', 8800, .25, 149, 80);
INSERT INTO employees VALUES ( 176, 'Jonathon', 'Taylor', 'JTAYLOR', '011.44.1644.429265', '24-MAR-1998', 'SA_REP', 8600, .20, 149, 80);
INSERT INTO employees VALUES ( 177, 'Jack', 'Livingston', 'JLIVINGS', '011.44.1644.429264', '23-APR-1998', 'SA_REP', 8400, .20, 149, 80);
INSERT INTO employees VALUES ( 178, 'Kimberely', 'Grant', 'KGRANT', '011.44.1644.429263', '24-MAY-1999', 'SA_REP', 7000, .15, 149, NULL);
INSERT INTO employees VALUES ( 179, 'Charles', 'Johnson', 'CJOHNSON', '011.44.1644.429262', '04-JAN-2000', 'SA_REP', 6200, .10, 149, 80);
INSERT INTO employees VALUES ( 180, 'Winston', 'Taylor', 'WTAYLOR', '650.507.9876', '24-JAN-1998', 'SH_CLERK', 3200, NULL, 120, 50);
INSERT INTO employees VALUES ( 181, 'Jean', 'Fleaur', 'JFLEAUR', '650.507.9877', '23-FEB-1998', 'SH_CLERK', 3100, NULL, 120, 50);
INSERT INTO employees VALUES ( 182, 'Martha', 'Sullivan', 'MSULLIVA', '650.507.9878', '21-JUN-1999', 'SH_CLERK', 2500, NULL, 120, 50);
INSERT INTO employees VALUES ( 183, 'Girard', 'Geoni', 'GGEONI', '650.507.9879', '03-FEB-2000', 'SH_CLERK', 2800, NULL, 120, 50);
INSERT INTO employees VALUES ( 184, 'Nandita', 'Sarchand', 'NSARCHAN', '650.509.1876', '27-JAN-1996', 'SH_CLERK', 4200, NULL, 121, 50);
INSERT INTO employees VALUES ( 185, 'Alexis', 'Bull', 'ABULL', '650.509.2876', '20-FEB-1997', 'SH_CLERK', 4100, NULL, 121, 50);
INSERT INTO employees VALUES ( 186, 'Julia', 'Dellinger', 'JDELLING', '650.509.3876', '24-JUN-1998', 'SH_CLERK', 3400, NULL, 121, 50);
INSERT INTO employees VALUES ( 187, 'Anthony', 'Cabrio', 'ACABRIO', '650.509.4876', '07-FEB-1999', 'SH_CLERK', 3000, NULL, 121, 50);
INSERT INTO employees VALUES ( 188, 'Kelly', 'Chung', 'KCHUNG', '650.505.1876', '14-JUN-1997', 'SH_CLERK', 3800, NULL, 122, 50);
INSERT INTO employees VALUES ( 189, 'Jennifer', 'Dilly', 'JDILLY', '650.505.2876', '13-AUG-1997', 'SH_CLERK', 3600, NULL, 122, 50);
INSERT INTO employees VALUES ( 190, 'Timothy', 'Gates', 'TGATES', '650.505.3876', '11-JUL-1998', 'SH_CLERK', 2900, NULL, 122, 50);
INSERT INTO employees VALUES ( 191, 'Randall', 'Perkins', 'RPERKINS', '650.505.4876', '19-DEC-1999', 'SH_CLERK', 2500, NULL, 122, 50);
INSERT INTO employees VALUES ( 192, 'Sarah', 'Bell', 'SBELL', '650.501.1876', '04-FEB-1996', 'SH_CLERK', 4000, NULL, 123, 50);
INSERT INTO employees VALUES ( 193, 'Britney', 'Everett', 'BEVERETT', '650.501.2876', '03-MAR-1997', 'SH_CLERK', 3900, NULL, 123, 50);
INSERT INTO employees VALUES ( 194, 'Samuel', 'McCain', 'SMCCAIN', '650.501.3876', '01-JUL-1998', 'SH_CLERK', 3200, NULL, 123, 50);
INSERT INTO employees VALUES ( 195, 'Vance', 'Jones', 'VJONES', '650.501.4876', '17-MAR-1999', 'SH_CLERK', 2800, NULL, 123, 50);
INSERT INTO employees VALUES ( 196, 'Alana', 'Walsh', 'AWALSH', '650.507.9811', '24-APR-1998', 'SH_CLERK', 3100, NULL, 124, 50);
INSERT INTO employees VALUES ( 197, 'Kevin', 'Feeney', 'KFEENEY', '650.507.9822', '23-MAY-1998', 'SH_CLERK', 3000, NULL, 124, 50);
INSERT INTO employees VALUES ( 198, 'Donald', 'OConnell', 'DOCONNEL', '650.507.9833', '21-JUN-1999', 'SH_CLERK', 2600, NULL, 124, 50);
INSERT INTO employees VALUES ( 199, 'Douglas', 'Grant', 'DGRANT', '650.507.9844', '13-JAN-2000', 'SH_CLERK', 2600, NULL, 124, 50);
INSERT INTO employees VALUES ( 200, 'Jennifer', 'Whalen', 'JWHALEN', '515.123.4444', '17-SEP-1987', 'AD_ASST', 4400, NULL, 101, 10);
INSERT INTO employees VALUES ( 201, 'Michael', 'Hartstein', 'MHARTSTE', '515.123.5555', '17-FEB-1996', 'MK_MAN', 13000, NULL, 100, 20);
INSERT INTO employees VALUES ( 202, 'Pat', 'Fay', 'PFAY', '603.123.6666', '17-AUG-1997', 'MK_REP', 6000, NULL, 201, 20);
INSERT INTO employees VALUES ( 203, 'Susan', 'Mavris', 'SMAVRIS', '515.123.7777', '07-JUN-1994', 'HR_REP', 6500, NULL, 101, 40);
INSERT INTO employees VALUES ( 204, 'Hermann', 'Baer', 'HBAER', '515.123.8888', '07-JUN-1994', 'PR_REP', 10000, NULL, 101, 70);
INSERT INTO employees VALUES ( 205, 'Shelley', 'Higgins', 'SHIGGINS', '515.123.8080', '07-JUN-1994', 'AC_MGR', 12000, NULL, 101, 110);
INSERT INTO employees VALUES ( 206, 'William', 'Gietz', 'WGIETZ', '515.123.8181', '07-JUN-1994', 'AC_ACCOUNT', 8300, NULL, 205, 110);

Creating Departments table

Here is a SQL snippet for creating the Departments table:

SQL

CREATE TABLE departments
    ( department_id int Primary key 
     ,department_name VARCHAR(30) NOT NULL
     ,manager_id  int
     ,location_id int
    )

Insert data into the Departments table:

SQL

INSERT INTO departments VALUES ( 10, 'Administration', 200, 1700);
INSERT INTO departments VALUES ( 20, 'Marketing', 201, 1800);
INSERT INTO departments VALUES ( 30, 'Purchasing', 114, 1700);
INSERT INTO departments VALUES ( 40, 'Human Resources', 203, 2400);
INSERT INTO departments VALUES ( 50, 'Shipping', 121, 1500);
INSERT INTO departments VALUES ( 60 , 'IT', 103, 1400);
INSERT INTO departments VALUES ( 70 , 'Public Relations', 204, 2700); 
INSERT INTO departments VALUES ( 80 , 'Sales', 145, 2500);
INSERT INTO departments VALUES ( 90 , 'Executive', 100, 1700);
INSERT INTO departments VALUES ( 100 , 'Finance', 108, 1700);
INSERT INTO departments VALUES ( 110 , 'Accounting', 205, 1700);
INSERT INTO departments VALUES ( 120 , 'Treasury', NULL, 1700);
INSERT INTO departments VALUES ( 130 , 'Corporate Tax', NULL, 1700);
INSERT INTO departments VALUES ( 140 , 'Control And Credit', NULL, 1700);
INSERT INTO departments VALUES ( 150 , 'Shareholder Services', NULL, 1700);
INSERT INTO departments VALUES ( 160 , 'Benefits', NULL, 1700);
INSERT INTO departments VALUES ( 170 , 'Manufacturing', NULL, 1700);
INSERT INTO departments VALUES ( 180 , 'Construction', NULL, 1700);
INSERT INTO departments VALUES ( 190 , 'Contracting', NULL, 1700);
INSERT INTO departments VALUES ( 200 , 'Operations', NULL, 1700);
INSERT INTO departments VALUES ( 210 , 'IT Support', NULL, 1700);
INSERT INTO departments VALUES ( 220 , 'NOC', NULL, 1700);
INSERT INTO departments VALUES ( 230 , 'IT Helpdesk', NULL, 1700);
INSERT INTO departments VALUES ( 240 , 'Government Sales', NULL, 1700);
INSERT INTO departments VALUES ( 250 , 'Retail Sales', NULL, 1700);
INSERT INTO departments VALUES ( 260 , 'Recruiting', NULL, 1700);
INSERT INTO departments VALUES ( 270 , 'Payroll', NULL, 1700);

Creating Regions table

Here is a SQL snippet for creating the Regions table:

SQL

CREATE TABLE regions
   ( region_id int Primary key CONSTRAINT region_id_nn NOT NULL,
     region_name VARCHAR(25) 
   );

Insert data into the regions table:

SQL

INSERT INTO regions VALUES ( 1, 'Europe' );
INSERT INTO regions VALUES ( 2, 'Americas');
INSERT INTO regions VALUES ( 3, 'Asia');
INSERT INTO regions VALUES ( 4, 'Middle East and Africa');

Creating Job_History table

Here is a SQL snippet for creating the Job_History table:

SQL

CREATE TABLE job_history
   ( employee_id int, 
     start_date DATE,
     end_date DATE,
     job_id VARCHAR(10),
     department_id int
   ) ;

Insert data into the Job_History table:

SQL

INSERT INTO job_history VALUES (102, '13-JAN-1993', '24-JUL-1998', 'IT_PROG', 60);
INSERT INTO job_history VALUES (101, '21-SEP-1989', '27-OCT-1993', 'AC_ACCOUNT', 110);
INSERT INTO job_history VALUES (101, '28-OCT-1993', '15-MAR-1997', 'AC_MGR', 110);
INSERT INTO job_history VALUES (201, '17-FEB-1996','19-DEC-1999', 'MK_REP', 20);
INSERT INTO job_history VALUES (114, '24-MAR-1998', '31-DEC-1999', 'ST_CLERK', 50);
INSERT INTO job_history VALUES (122, '01-JAN-1999', '31-DEC-1999', 'ST_CLERK', 50);
INSERT INTO job_history VALUES (200, '17-SEP-1987', '17-JUN-1993', 'AD_ASST', 90);
INSERT INTO job_history VALUES (176,'24-MAR-1998', '31-DEC-1998', 'SA_REP', 80);
INSERT INTO job_history VALUES (176, '01-JAN-1999', '31-DEC-1999', 'SA_MAN', 80);
INSERT INTO job_history VALUES (200, '01-JUL-1994', '31-DEC-1998', 'AC_ACCOUNT', 90);

Creating Jobs table

Here is a SQL snippet for creating the Jobs table:

SQL

CREATE TABLE jobs
   ( job_id varchar(10) Primary key
   , job_title VARCHAR(35) NOT NULL
   , min_salary money
   , max_salary money
   ) ;

Insert data into the Jobs table:

SQL

INSERT INTO jobs VALUES ( 'AD_PRES', 'President', 20000, 40000);
INSERT INTO jobs VALUES ( 'AD_VP', 'Administration Vice President', 15000, 30000);
INSERT INTO jobs VALUES ( 'AD_ASST', 'Administration Assistant', 3000, 6000);
INSERT INTO jobs VALUES ( 'FI_MGR', 'Finance Manager', 8200, 16000);
INSERT INTO jobs VALUES ( 'FI_ACCOUNT', 'Accountant', 4200, 9000);
INSERT INTO jobs VALUES ( 'AC_MGR', 'Accounting Manager', 8200, 16000);
INSERT INTO jobs VALUES ( 'AC_ACCOUNT', 'Public Accountant', 4200, 9000);
INSERT INTO jobs VALUES ( 'SA_MAN', 'Sales Manager', 10000, 20000);
INSERT INTO jobs VALUES ( 'SA_REP', 'Sales Representative', 6000, 12000);
INSERT INTO jobs VALUES ( 'PU_MAN', 'Purchasing Manager', 8000, 15000);
INSERT INTO jobs VALUES ( 'PU_CLERK', 'Purchasing Clerk', 2500, 5500);
INSERT INTO jobs VALUES ( 'ST_MAN', 'Stock Manager', 5500, 8500);
INSERT INTO jobs VALUES ( 'ST_CLERK', 'Stock Clerk', 2000, 5000);
INSERT INTO jobs VALUES ( 'SH_CLERK', 'Shipping Clerk', 2500, 5500);
INSERT INTO jobs VALUES ( 'IT_PROG', 'Programmer', 4000, 10000);
INSERT INTO jobs VALUES ( 'MK_MAN', 'Marketing Manager', 9000, 15000);
INSERT INTO jobs VALUES ( 'MK_REP', 'Marketing Representative', 4000, 9000);
INSERT INTO jobs VALUES ( 'HR_REP', 'Human Resources Representative', 4000, 9000);
INSERT INTO jobs VALUES ( 'PR_REP', 'Public Relations Representative', 4500, 10500);

Creating Locations table

Here is a SQL snippet for creating the Locations table:

SQL

  CREATE TABLE locations
   ( location_id int primary key
   , street_address VARCHAR(40)
   , postal_code VARCHAR(12)
   , city VARCHAR(30) NOT NULL
   , state_province VARCHAR(25)
   , country_id CHAR(2)
   ) ;

Insert data into the Locations table:

SQL

INSERT INTO locations VALUES ( 1000 , '1297 Via Cola di Rie', '00989', 'Roma', NULL, 'IT');
INSERT INTO locations VALUES ( 1100 , '93091 Calle della Testa', '10934', 'Venice', NULL, 'IT');
INSERT INTO locations VALUES ( 1200 , '2017 Shinjuku-ku', '1689', 'Tokyo', 'Tokyo Prefecture', 'JP');
INSERT INTO locations VALUES ( 1300 , '9450 Kamiya-cho', '6823', 'Hiroshima', NULL, 'JP');
INSERT INTO locations VALUES ( 1400 , '2014 Jabberwocky Rd', '26192', 'Southlake', 'Texas', 'US');
INSERT INTO locations VALUES ( 1500 , '2011 Interiors Blvd', '99236', 'South San Francisco', 'California', 'US');
INSERT INTO locations VALUES ( 1600 , '2007 Zagora St', '50090', 'South Brunswick', 'New Jersey', 'US');
INSERT INTO locations VALUES ( 1700 , '2004 Charade Rd', '98199', 'Seattle', 'Washington', 'US');
INSERT INTO locations VALUES ( 1800 , '147 Spadina Ave', 'M5V 2L7', 'Toronto', 'Ontario', 'CA');
INSERT INTO locations VALUES ( 1900 , '6092 Boxwood St', 'YSW 9T2', 'Whitehorse', 'Yukon', 'CA');
INSERT INTO locations VALUES ( 2000 , '40-5-12 Laogianggen', '190518', 'Beijing', NULL, 'CN');
INSERT INTO locations VALUES ( 2100 , '1298 Vileparle (E)', '490231', 'Bombay', 'Maharashtra', 'IN');
INSERT INTO locations VALUES ( 2200 , '12-98 Victoria Street', '2901', 'Sydney', 'New South Wales', 'AU');
INSERT INTO locations VALUES ( 2300 , '198 Clementi North', '540198', 'Singapore', NULL, 'SG');
INSERT INTO locations VALUES ( 2400 , '8204 Arthur St', NULL, 'London', NULL, 'UK');
INSERT INTO locations VALUES ( 2500 , 'Magdalen Centre, The Oxford Science Park', 'OX9 9ZB', 'Oxford', 'Oxford', 'UK');
INSERT INTO locations VALUES ( 2600 , '9702 Chester Road', '09629850293', 'Stretford', 'Manchester', 'UK');
INSERT INTO locations VALUES ( 2700 , 'Schwanthalerstr. 7031', '80925', 'Munich', 'Bavaria', 'DE');
INSERT INTO locations VALUES ( 2800 , 'Rua Frei Caneca 1360 ', '01307-002', 'Sao Paulo', 'Sao Paulo', 'BR');
INSERT INTO locations VALUES ( 2900 , '20 Rue des Corps-Saints', '1730', 'Geneva', 'Geneve', 'CH');
INSERT INTO locations VALUES ( 3000 , 'Murtenstrasse 921', '3095', 'Bern', 'BE', 'CH');
INSERT INTO locations VALUES ( 3100 , 'Pieter Breughelstraat 837', '3029SK', 'Utrecht', 'Utrecht', 'NL');
INSERT INTO locations VALUES ( 3200 , 'Mariano Escobedo 9991', '11932', 'Mexico City', 'Distrito Federal,', 'MX');

Creating Countries table

Here is a SQL snippet for creating the Countries table:

SQL

   CREATE TABLE countries 
   ( country_id CHAR(2) Primary key 
   , country_name VARCHAR(40) 
   , region_id int
   )

Insert data into the Countries table:

SQL

INSERT INTO countries VALUES ( 'IT', 'Italy', 1 );
INSERT INTO countries VALUES ( 'JP', 'Japan', 3 );
INSERT INTO countries VALUES ( 'US', 'United States of America', 2 );
INSERT INTO countries VALUES ( 'CA', 'Canada', 2 );
INSERT INTO countries VALUES ( 'CN', 'China', 3 );
INSERT INTO countries VALUES ( 'IN', 'India', 3 );
INSERT INTO countries VALUES ( 'AU', 'Australia', 3 );
INSERT INTO countries VALUES ( 'ZW', 'Zimbabwe', 4 );
INSERT INTO countries VALUES ( 'SG', 'Singapore', 3 );
INSERT INTO countries VALUES ( 'UK', 'United Kingdom', 1 );
INSERT INTO countries VALUES ( 'FR', 'France', 1 );
INSERT INTO countries VALUES ( 'DE', 'Germany', 1 );
INSERT INTO countries VALUES ( 'ZM', 'Zambia', 4 );
INSERT INTO countries VALUES ( 'EG', 'Egypt', 4 );
INSERT INTO countries VALUES ( 'BR', 'Brazil', 2 );
INSERT INTO countries VALUES ( 'CH', 'Switzerland', 1 );
INSERT INTO countries VALUES ( 'NL', 'Netherlands', 1 );
INSERT INTO countries VALUES ( 'MX', 'Mexico', 2 );
INSERT INTO countries VALUES ( 'KW', 'Kuwait', 4  );
INSERT INTO countries VALUES ( 'IL', 'Israel', 4 );
INSERT INTO countries VALUES ( 'DK', 'Denmark', 1 );
INSERT INTO countries VALUES ( 'HK', 'HongKong', 3 );
INSERT INTO countries VALUES ( 'NG', 'Nigeria', 4 );
INSERT INTO countries VALUES ( 'AR', 'Argentina', 2 );
INSERT INTO countries VALUES ( 'BE' , 'Belgium', 1 );

Step 2: Defining Relationships Between Tables

To ensure data consistency, establish relationships between the tables using foreign key constraints:

SQL

alter table employees add foreign key ( job_id)references Jobs (job_id)
---------------------------------------------------------------------------------------
alter table departments add foreign key(Location_id) references locations (location_id)
---------------------------------------------------------------------------------------
alter table countries add foreign key (region_id) references regions (region_id)
---------------------------------------------------------------------------------------
alter table locations add foreign key (country_id) references countries (country_id)
---------------------------------------------------------------------------------------
alter table Job_History add foreign key (job_id) references jobs (job_id)
---------------------------------------------------------------------------------------
alter table job_history add foreign key (department_id) references departments (department_id)

This command links the Employees table to the Jobs table, enforcing that every employee must have a valid job role.

Step 3: Writing and Executing SQL Queries

Now that the database is set up, we can use SQL queries to extract meaningful insights. Below are some key queries and their purposes:

Retrieve all employees in a specific department.

SQL

      SELECT 
      			 [first_name]
      			,[last_name]
      			,[department_name]
  		FROM [HRSchema].[dbo].[employees] e
  		inner join departments d  on e.department_id = d.department_id

Calculate the average salary in each department.

SQL

  SELECT     
      department_name, round(avg(salary) , 2) avg_salary
  FROM [HRSchema].[dbo].[employees] e
  inner join departments d
  on e.department_id = d.department_id 
  group by department_name

List employees who were hired in the year of 1999.

SQL

  Select last_name, Year(hire_date) as years
  from employees 
  where Year(hire_date) = 1999

Write a query to find employees who have never worked in the “Sales” department throughout their job history.

SQL

SELECT e.employee_id, e.first_name, e.last_name
FROM employees e
WHERE NOT EXISTS (
    SELECT 1
    FROM job_history jh
    JOIN departments d ON jh.department_id = d.department_id
    WHERE jh.employee_id = e.employee_id
    AND d.department_name = 'Sales'
);

Calculate the average salary for each region and compare it with the average salary within each department of that region.

SQL

---Calculate the average salary for each region:
WITH RegionAvgSalaries AS (
    SELECT r.region_id, r.region_name, AVG(e.salary) AS avg_region_salary
    FROM employees e
    JOIN departments d ON e.department_id = d.department_id
    JOIN locations l ON d.location_id = l.location_id
    JOIN countries c ON l.country_id = c.country_id
    JOIN regions r ON c.region_id = r.region_id
    GROUP BY r.region_id, r.region_name
)

SELECT * FROM RegionAvgSalaries;

---Calculate the average salary within each department of each region:
WITH DepartmentAvgSalaries AS (
    SELECT r.region_id, r.region_name, d.department_id, AVG(e.salary) AS avg_dept_salary
    FROM employees e
    JOIN departments d ON e.department_id = d.department_id
    JOIN locations l ON d.location_id = l.location_id
    JOIN countries c ON l.country_id = c.country_id
    JOIN regions r ON c.region_id = r.region_id
    GROUP BY r.region_id, r.region_name, d.department_id
)

SELECT * FROM DepartmentAvgSalaries;


	---Combine results to compare average salaries within regions and departments:
			
WITH RegionAvgSalaries AS (
    	SELECT r.region_id, r.region_name, AVG(e.salary) AS avg_region_salary
    FROM employees e
    JOIN departments d ON e.department_id = d.department_id
    JOIN locations l ON d.location_id = l.location_id
    JOIN countries c ON l.country_id = c.country_id
    JOIN regions r ON c.region_id = r.region_id
    GROUP BY r.region_id, r.region_name
),
DepartmentAvgSalaries AS (
    SELECT r.region_id, r.region_name, d.department_id, AVG(e.salary) AS avg_dept_salary
    FROM employees e
    JOIN departments d ON e.department_id = d.department_id
    JOIN locations l ON d.location_id = l.location_id
    JOIN countries c ON l.country_id = c.country_id
    JOIN regions r ON c.region_id = r.region_id
    GROUP BY r.region_id, r.region_name, d.department_id
)

SELECT da.region_name, da.department_id, da.avg_dept_salary, ra.avg_region_salary
FROM DepartmentAvgSalaries da
JOIN RegionAvgSalaries ra ON da.region_id = ra.region_id;

Determine how many employees are located in each country and list the top 3 countries with the highest number of employees working in the “IT” job category.

SQL

SELECT 
    c.country_name,
    COUNT(e.employee_id) AS total_employees
FROM 
    employees e
JOIN 
    departments d ON e.department_id = d.department_id
JOIN 
    locations l ON d.location_id = l.location_id
JOIN 
    countries c ON l.country_id = c.country_id
GROUP BY 
    c.country_name;
------------------------------------

	SELECT TOP 3
    c.country_name,
    COUNT(e.employee_id) AS it_employees
FROM 
    employees e
JOIN 
    departments d ON e.department_id = d.department_id
JOIN 
    locations l ON d.location_id = l.location_id
JOIN 
    countries c ON l.country_id = c.country_id
--JOIN 
    --jobs j ON e.job_id = j.job_id
WHERE 
department_name = 'IT'
    --j.job_title = 'IT'
GROUP BY 
    c.country_name
ORDER BY 
    it_employees DESC;

Select * from jobs

Find employees with the longest tenure in the company and list each of their job titles along with the duration they held each job.

SQL

         ------------------ Find employees with the longest tenure in the company
	WITH EmployeeTenure AS (
    SELECT 
        e.employee_id,
        SUM(DATEDIFF(DAY, jh.start_date, ISNULL(jh.end_date, GETDATE()))) AS total_days
    FROM 
        employees e
    LEFT JOIN 
        job_history jh ON e.employee_id = jh.employee_id
    GROUP BY 
        e.employee_id
)

SELECT TOP 1
    et.employee_id,
    et.total_days
FROM 
    EmployeeTenure et
ORDER BY 
    et.total_days DESC;
------------------- List each of their job titles along with the duration they held each job
WITH EmployeeTenure AS (
    SELECT 
        e.employee_id,
        SUM(DATEDIFF(DAY, jh.start_date, ISNULL(jh.end_date, GETDATE()))) AS total_days
    FROM 
        employees e
    LEFT JOIN 
        job_history jh ON e.employee_id = jh.employee_id
    GROUP BY 
        e.employee_id
),
LongestTenureEmployee AS (
    SELECT TOP 1
        et.employee_id
    FROM 
        EmployeeTenure et
    ORDER BY 
        et.total_days DESC
)

SELECT 
    jh.employee_id,
    j.job_title,
    DATEDIFF(DAY, jh.start_date, ISNULL(jh.end_date, GETDATE())) AS duration_days
FROM 
    job_history jh
JOIN 
    jobs j ON jh.job_id = j.job_id
WHERE 
    jh.employee_id = (SELECT employee_id FROM LongestTenureEmployee)
ORDER BY 
    jh.start_date;

Analyze how the number of employees in each department has changed over the years. Visualize which departments have grown or shrunk significantly.

SQL


WITH EmployeeYearlyData AS (
    SELECT 
        YEAR(jh.start_date) AS year,
        jh.department_id,
        COUNT(DISTINCT jh.employee_id) AS employee_count
    FROM 
        job_history jh
    GROUP BY 
        YEAR(jh.start_date), jh.department_id
),
CurrentEmployees AS (
    SELECT 
        YEAR(GETDATE()) AS year,
        e.department_id,
        COUNT(DISTINCT e.employee_id) AS employee_count
    FROM 
        employees e
    GROUP BY 
        e.department_id
)

SELECT
    CASE 
        WHEN eyd.department_id IS NOT NULL THEN eyd.year
        ELSE ce.year
    END AS year,
    d.department_name,
    ISNULL(eyd.employee_count, 0) + ISNULL(ce.employee_count, 0) AS employee_count
FROM 
    EmployeeYearlyData eyd
FULL OUTER JOIN 
    CurrentEmployees ce ON eyd.department_id = ce.department_id
JOIN 
    departments d ON ISNULL(eyd.department_id, ce.department_id) = d.department_id
ORDER BY 
    year, department_name;

Compare the highest and lowest-paid employees across different locations. Determine if there’s a noticeable salary variation between different locations in the same country.

SQL

WITH LocationSalaries AS (
    SELECT 
        l.location_id,
        c.country_name,
        MAX(e.salary) AS max_salary,
        MIN(e.salary) AS min_salary
    FROM 
        employees e
    JOIN 
        departments d ON e.department_id = d.department_id  -- 
    JOIN 
        locations l ON d.location_id = l.location_id
    JOIN 
        countries c ON l.country_id = c.country_id
    GROUP BY 
        l.location_id, c.country_name
),
CountrySalaryStats AS (
    SELECT 
        country_name,
        MAX(max_salary) AS highest_salary,
        MIN(min_salary) AS lowest_salary
    FROM 
        LocationSalaries
    GROUP BY 
        country_name
)

SELECT 
    ls.country_name,
    ls.location_id,
    ls.max_salary,
    ls.min_salary,
    cs.highest_salary,
    cs.lowest_salary
FROM 
    LocationSalaries ls
JOIN 
    CountrySalaryStats cs ON ls.country_name = cs.country_name
ORDER BY 
    ls.country_name, ls.location_id;

Analyze hiring trends to determine which months consistently see the highest number of new hires. Consider if this trend changes across different departments.

SQL

	WITH MonthlyHires AS (
    SELECT 
        YEAR(hire_date) AS hire_year,
        MONTH(hire_date) AS hire_month,
        department_id,
        COUNT(employee_id) AS hires_count
    FROM 
        employees
    WHERE 
        hire_date IS NOT NULL
    GROUP BY 
        YEAR(hire_date), MONTH(hire_date), department_id
),
AverageMonthlyHires AS (
    SELECT 
        hire_month,
        department_id,
        AVG(hires_count * 1.0) AS avg_hires
    FROM 
        MonthlyHires
    GROUP BY 
        hire_month, department_id
)

SELECT 
    d.department_name,
    amh.hire_month,
    amh.avg_hires
FROM 
    AverageMonthlyHires amh
JOIN 
    departments d ON amh.department_id = d.department_id
ORDER BY 
    amh.department_id, amh.avg_hires DESC;

Write a report on the distribution of employees across regions for a specific job category, and discuss any notable patterns in diversity.

SQL

DECLARE @JobTitle VARCHAR(100) = 'Accounting Manager';  -- Replace with desired job title

WITH EmployeeRegions AS (
    SELECT 
        r.region_name,
        j.job_title,
        COUNT(e.employee_id) AS employee_count
    FROM 
        employees e
    JOIN 
        jobs j ON e.job_id = j.job_id
    JOIN 
        departments d ON e.department_id = d.department_id
    JOIN 
        locations l ON d.location_id = l.location_id
    JOIN 
        countries c ON l.country_id = c.country_id
    JOIN 
        regions r ON c.region_id = r.region_id
    WHERE 
        j.job_title = @JobTitle
    GROUP BY 
        r.region_name, j.job_title
)

SELECT 
    region_name,
    employee_count
FROM 
    EmployeeRegions
ORDER BY 
    employee_count DESC

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