A subquery, also known as a nested query or subselect, is a SELECT query embedded within the WHERE or HAVING clause of another SQL query. The data returned by the subquery is used by the outer statement in the same way a literal value would be used. ... A subquery must return only one column.
For more information visit https://tutsmaster.org/
A subquery, also known as a nested query or subselect, is a SELECT query embedded within the WHERE or HAVING clause of another SQL query. The data returned by the subquery is used by the outer statement in the same way a literal value would be used. ... A subquery must return only one column.
For more information visit https://tutsmaster.org/
Entity type
Entity sets
Attributes and keys
Relationship model
Mapping Constraints
The ER Model
Cardinality Constraints
Generalization, Specialization and Aggregation
ER Diagram & Database design with the ER Model
Introduction
Relational Model
Concepts
Characteristics
This is a presentation on LALR parser. This presentation was created by 6th sem CSE student.
LALR parser is basically used to creating the LR parsing table. LALR parser is used because it is more powerful than SLR and the tables generated by LALR consumes less memory and disk space than CLR parser.
BackTracking Algorithm: Technique and ExamplesFahim Ferdous
This slides gives a strong overview of backtracking algorithm. How it came and general approaches of the techniques. Also some well-known problem and solution of backtracking algorithm.
Artificial Intelligence: Introduction, Typical Applications. State Space Search: Depth Bounded
DFS, Depth First Iterative Deepening. Heuristic Search: Heuristic Functions, Best First Search,
Hill Climbing, Variable Neighborhood Descent, Beam Search, Tabu Search. Optimal Search: A
*
algorithm, Iterative Deepening A*
, Recursive Best First Search, Pruning the CLOSED and OPEN
Lists
Entity type
Entity sets
Attributes and keys
Relationship model
Mapping Constraints
The ER Model
Cardinality Constraints
Generalization, Specialization and Aggregation
ER Diagram & Database design with the ER Model
Introduction
Relational Model
Concepts
Characteristics
This is a presentation on LALR parser. This presentation was created by 6th sem CSE student.
LALR parser is basically used to creating the LR parsing table. LALR parser is used because it is more powerful than SLR and the tables generated by LALR consumes less memory and disk space than CLR parser.
BackTracking Algorithm: Technique and ExamplesFahim Ferdous
This slides gives a strong overview of backtracking algorithm. How it came and general approaches of the techniques. Also some well-known problem and solution of backtracking algorithm.
Artificial Intelligence: Introduction, Typical Applications. State Space Search: Depth Bounded
DFS, Depth First Iterative Deepening. Heuristic Search: Heuristic Functions, Best First Search,
Hill Climbing, Variable Neighborhood Descent, Beam Search, Tabu Search. Optimal Search: A
*
algorithm, Iterative Deepening A*
, Recursive Best First Search, Pruning the CLOSED and OPEN
Lists
Review the SHRM case Designing a Pay Structure” You will p.docxfathwaitewalter
Review the SHRM case: “
Designing a Pay Structure
”
You will prepare the SHRM case analysis on “Designing a Pay Structure” which consists of your completion of Tasks A–J that simulates the creation of a compensation system for an organization in meeting its goals and supporting its mission. In your analysis, respond to the following tasks found in the case study.
Your case analysis should consist of:
Task A:
Create a complete job description for the Benefits Manager position using O*NET.
Task B:
Calculate the job evaluation points for the administrative assistant, payroll assistant, operational analyst, and benefits manager jobs. Provide a rationale for assigning specific degrees to the various jobs.
Task C:
If there were any outliers (i.e., extreme data points) in the data, what would you recommend doing with them? From this point forward, assume no extreme data points exist in the dataset.
Task D:
Conduct a simple regression in Excel to create a market pay line by entering the job evaluation points (on the X axis) and the respective weighted average market base pay (on the Y axis) for each benchmark job.
Task E:
What is your R squared (variance explained)? Is it sufficient to proceed?
Task F:
Calculate the predicted base pay for each benchmark job.
Task G:
Because your company wants to lead in base pay by 3 percent, adjust the predicted pay rates to determine the base pay rate you will offer for each benchmark job.
Task H:
Create pay grades by combining any benchmark jobs that are substantially comparable for pay purposes. Clearly label your pay grades and explain why you combined any benchmark jobs to form a grade.
Task I:
Use your answer to Task H to determine the pay range (i.e., minimum and maximum) for each pay grade.
Task J:
Given the pay structure you have generated, consider the following: Does this pay structure make good business sense? Do you think it is consistent with the organization’s business strategy? What are the implications of this pay structure for other HR systems, such as retention and recruiting?
Your analysis of this case and your written submission should reflect an understanding of the critical issues of the case, integrating the material covered in the text, and present concise and well-reasoned justifications for the stance that you take. You are to complete this case analysis using Excel in a spreadsheet analysis format.
You may discuss your case analysis Assignment with the class, but you must submit your own original work.
Case analysis tips:
Avoid common errors in case analyses, such as:
● Focusing too heavily on minor issues.
● Lamenting because of insufficient data in the case and ignoring creative alternatives.
● Rehashing of case data — you should assume the reader knows the case.
● Not appropriately evaluating the quality of the case's data.
● Obscuring the quantitative analysis or making it difficult to understand.
Typical “minus (–)” grades result from su ...
Chapter 1 TestSuppose that you are an administrator in a .docxsleeperharwell
Chapter 1: Test
Suppose that you are an administrator in a health care facility and you want to
compare the admission heart rate (in beats per minute, bpm) of adult women ages
30–40 who are current residents. You want to try out your Excel skills on a small
random sample of residents. The hypothetical data is given below (see Fig. B.1).
(a) Create an Excel table for these data, and then use Excel to the right of the table
to find the sample size, mean, standard deviation, and standard error of the
mean for these data. Label your answers, and round off the mean, standard
deviation, and standard error of the mean to two decimal places.
(b) Save the file as: BEATS3
Chapter 2: Test
A health care facility has discharged 124 patients within the last 60 days. Suppose
that you want to do a Customer Satisfaction Survey on a random sample of 20 of
these 124 patients for this survey.
(a) Set up a spreadsheet of frame numbers for these patients with the heading:
FRAME NUMBERS
Fig. B.1 Worksheet Data
for Chap. 1 Test (Practical
Example)
(b) Then, create a separate column to the right of these frame numbers which
duplicates these frame numbers with the title: Duplicate frame numbers.
(c) Then, create a separate column to the right of these duplicate frame numbers
called RAND NO. and use the ¼RAND() function to assign random numbers to
all of the frame numbers in the duplicate frame numbers column. Change this
column format so that three decimal places appear for each random number.
(d) Sort the duplicate frame numbers and random numbers into a random order.
(e) Print the result so that the spreadsheet fits onto one page.
(f) Circle on your printout the I.D. number of the first 20 patients that you would
use in your survey.
(g) Save the file as: RAND58
Important note: Everyone who does this problem will generate a different
random order of patient ID numbers since Excel assigns a
different random number each time the RAND() command is
used. For this reason, the answer to this problem given in this
Excel Guide will have a completely different sequence of
random numbers from the random sequence that you generate.
This is normal and is to be expected.
Chapter 3: Test
Suppose that you are an administrator at a health care clinic facility and want to find
out how the wages of a specific type of technician in your facility compare to the
average wages of similar technicians in the city and county of St. Louis, Missouri,
USA. The current average wage for this type of technician in your facility is $25.00
per hour. You have been asked to “run the data” to see how this wage compares to
those in St. Louis. You have decided to test your Excel skills on a random sample of
technicians in St. Louis and you have created the hypothetical data given in Fig. B.2
(a) Create an Excel table for these data, and use Excel to the right of the table to
find the sample size, mean, standard deviation, and standard error of the mean
for these.
James Colby Maddox Business Intellignece and Computer Science Portfoliocolbydaman
This portfolio covers the business intelligence course work I have completed at Set Focus, and some of the course work I have completed at Kennesaw State University
Ace the C_THR92_2305 Certification Exam - Expert Preparation GuideAliza Oscar
Get ready to excel in the C_THR92_2305 certification exam with our comprehensive preparation guide. Master key concepts, practice with real exam questions, and boost your confidence for success in the C_THR92_2305 exam
C_THR87_2305 Certification Exam Validate Your HR ExpertiseAliza Oscar
Prepare for the C_THR87_2305 certification exam to showcase your advanced skills in Human Resources. Demonstrate your proficiency in HR processes and technologies, and elevate your career prospects in the field.
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
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Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
2. SQL and E-R diagram related
problems and its solution.
7/11/2016 2Prepared By- Shimul & Hirok,CSE,MBSTU
Presentation on……
Presented By
• NAME : ID:
• MD.MAHBUBUR RAHMAN CE-12038
• HIROK BISWAS CE-12032
3. We are going to talking about
SQL expressions:
sample bank database(3.19)
relational schema(3.21,3.22)
E-R diagram for a hospital(6.15)
UML equivalents of the E-R diagrams(6.28)
Conclution
7/11/2016 Prepared By- Shimul & Hirok,CSE,MBSTU 3
4. Problem 1 :
Using the relations of our sample bank database, write SQL expressions to
define the following views:
a. A view containing the account numbers and customer names (but not the
balances) for all accounts at the Deer Park branch.
b. A view containing the names and addresses of all customers who have an
account with the bank, but do not have a loan.
c. A view containing the name and average account balance of every customer
of the Rock Ridge branch.
5. Solution of Problem 1 (a)
A view containing the account numbers and customer names (but not
the balances) for all accounts at the Deer Park branch.
Table: accountTable: depositor
7/11/2016 5Prepared By- Shimul & Hirok,CSE,MBSTU
6. Solution of Problem 1 (a)( Cont…)
• Query:
select depositor.customer_name,depositor.account_number
from depositor,account
where depositor.account_number =account.account_number
and account.branch_name='Deer Park';
• Table view:
7/11/2016 6Prepared By- Shimul & Hirok,CSE,MBSTU
7. Solution of Problem 1 (b)
A view containing the names and addresses of all customers who have
an account with the bank, but do not have a borrower.
Table: customer Table: depositor Table: borrower
7/11/2016 7Prepared By- Shimul & Hirok,CSE,MBSTU
8. Solution of Problem 1 (b)(Cont…)
select c.customer_name, c.customer_street,
c.customer_city
from customer c, depositor d
where c.customer_name not in (select
customer_name
from borrower)
and c.customer_name = d.customer_name;
• Query:
• Table view:
7/11/2016 8Prepared By- Shimul & Hirok,CSE,MBSTU
9. Solution of Problem 1 (c)
. A view containing the name and average account balance of every
customer of the 'sidney' branch.
Table: account Table: depositor
7/11/2016 9Prepared By- Shimul & Hirok,CSE,MBSTU
10. Solution of Problem 1 (c) (Cont…)
select customer_name, avg(a.balance)
from account a, depositor d
where a.account_number = d.account_number
and branch_name='sidney'
group by customer_name;
• Query:
• Table view:
7/11/2016 10Prepared By- Shimul & Hirok,CSE,MBSTU
11. Problem 1 (EXP-02) :
create procedure get_emp(employee_id in varchar(10))
return char
BEGIN
select employee.employee_id,department.department_name,salary.salary_scale,salary.salary_amount from department
inner join employee_department on department.department_id=employee_department.department_id
inner join employee on employee.employee_id=employee_department.employee_id
inner join employee_salary on employee.employee_id=employee_salary.employee_id
inner join salary on salary.salary_scale=employee_salary.salary_scale
where employee.employee_id=employee_id;
return(employee_id);
END;
Exec get_emp('emp02');
Solution of Problem 1 (Exp-2):
Create a procedure that will take Employee_ID it’s parameter return
Employee_ID ,Department_Name, Salary_Scale and Salary_Amount.
7/11/2016 11Prepared By- Shimul & Hirok,CSE,MBSTU
12. Problem 2 :
Consider the following relational schema
employee(emp_no , name, office, age)
books(isbn , title, authors, publisher)
loan(emp_no , isbn, date)
Write the following queries in SQL.
a. Print the names of employees who have borrowed any book published by
McGraw-Hill.
b. Print the names of employees who have borrowed all books published by
McGraw-Hill.
c. For each publisher, print the names of employees who have borrowed more than five
books of that publisher.
7/11/2016 12Prepared By- Shimul & Hirok,CSE,MBSTU
13. Solution of Problem 2 (a)
Print the names of employees who have borrowed any book published
by McGraw-Hill.
Table: employee
Table: books
Table: loan
7/11/2016 13Prepared By- Shimul & Hirok,CSE,MBSTU
14. Solution of Problem 2 (a) (cont…)
• Query:
select distinct name as employee_name from employee
inner join loan on employee.emp_no=loan.emp_no
inner join books on loan.isbn=books.isbn
where books.publisher='Mcgraw-hill';
• Table view:
7/11/2016 14Prepared By- Shimul & Hirok,CSE,MBSTU
15. Solution of Problem 2 (b)
Print the names of employees who have borrowed all book published
by McGraw-Hill.
Table: employee
Table: books
Table: loan
result
7/11/2016 15Prepared By- Shimul & Hirok,CSE,MBSTU
16. Solution of Problem 2 (b) (cont…)
• Query:
select distinct name as employee_name from employee
inner join loan on employee.emp_no=loan.emp_no
inner join books on loan.isbn=books.isbn
where (select count(loan.isbn) from loan where
loan.emp_no=employee.emp_no)=(select count(books.isbn) from books
where books.publisher='Mcgraw-hill');
• Table view:
7/11/2016 16Prepared By- Shimul & Hirok,CSE,MBSTU
17. Solution of Problem 2 (c)
For each publisher, print the names of employees who have borrowed
more than five books of that publisher.
Table: employee
Table: books
Table: loan
result
More than
5
Books from
Mcgraw-hill
(only)
7/11/2016 17Prepared By- Shimul & Hirok,CSE,MBSTU
18. Solution of Problem 2 (c) (cont…)
• Query:
select name from employee,loan,books
where employee.emp_no=loan.emp_no and
books.isbn=loan.isbn
group by employee.emp_no,name,books.publisher having
count(loan.isbn) >=5;
• Table view:
7/11/2016 18Prepared By- Shimul & Hirok,CSE,MBSTU
19. Problem 3 :
Consider the relational schema
student(student_id , student_name)
registerd(student_id , course_id)
Write an SQL query to list the student-id and name of each
student along with the total number of courses that the student is
registered for. Students who are not registerd for any course must
also be listed, with the number of registerd
courses shown as 0.
7/11/2016 19Prepared By- Shimul & Hirok,CSE,MBSTU
20. Solution of Problem 3
Table: student
Table: registerd
a is registerd by
3
course
b is registerd by
1
course
C is not
registerd
(0)
7/11/2016 20Prepared By- Shimul & Hirok,CSE,MBSTU
21. Solution of Problem 3 (cont…)
• Query:
select student_id,student_name,(select count(registerd.course_id) from registerd
where student.student_id=registerd.student_id) as taken_course
from student;
• Table view:
7/11/2016 21Prepared By- Shimul & Hirok,CSE,MBSTU
22. Problem 4:
Consider the relational schema:
Department (Department _ID , Department _Name)
Employee (Employee_ID , Employee_Name,Employee_Age)
Employee _Department( Employee _ID , Department _ID )
Salary (Salary _Scale , Salary _Amount)
Employee_ Salary (Employee _ID , Salary _Scale)
a) Find the Department_names where the employee’s average salary is more
than 10000.
b) Find the employee_names who has paid in salary scale 1.
c) Update the employee ages by increasing 10 years whose ages are not equal
to average age.
7/11/2016 22Prepared By- Shimul & Hirok,CSE,MBSTU
23. Solution of Problem 4 (a)
Find the Department_names where the employee’s average salary is more
than 10000.
Table: department Table: employee_department
Table: employee_salary
Table: salary
7/11/2016 23Prepared By- Shimul & Hirok,CSE,MBSTU
24. Solution of Problem 4(a) (cont…)
• Query:
select department_name,avg(salary.salary_amount) from department
inner join employee_department on
department.department_id=employee_department.department_id
inner join employee_salary on
employee_department.employee_id=employee_salary.employee_id
inner join salary on salary.salary_scale=employee_salary.salary_scale
having avg(salary.salary_amount)>10000
group by department.department_name;
• Table view:
7/11/2016 24Prepared By- Shimul & Hirok,CSE,MBSTU
25. Solution of Problem 4 (b)
Find the employee_names who has paid in salary scale 1.
Table: Employee Table: employee_salary
Table: salary
result
7/11/2016 25Prepared By- Shimul & Hirok,CSE,MBSTU
26. Solution of Problem 4(b) (cont…)
• Query:
select employee_name from employee inner join employee_salary
on employee_salary.employee_id=employee.employee_id
inner join salary on salary.salary_scale=employee_salary.salary_scale
where salary.salary_scale=1;
• Table view:
7/11/2016 26Prepared By- Shimul & Hirok,CSE,MBSTU
27. Solution of Problem 4(c)
• Query:
update employee
set employee.employee_age=employee.employee_age+1
where employee.employee_age not in (select avg(employee.employee_age) from employee);
• Table view:
Before update:
After update:
Average
age
7/11/2016 27Prepared By- Shimul & Hirok,CSE,MBSTU
28. Problem 5
Construct an E-R diagram for a hospital with a
set of patients and a set of medical doctors.
Associate with each patient a log of the
various tests and examinations conducted.
7/11/2016 28Prepared By- Shimul & Hirok,CSE,MBSTU
29. Solution Of problem 5:
Fig: E-R diagram for a hospital system.
7/11/2016 29Prepared By- Shimul & Hirok,CSE,MBSTU
30. Problem 6
Draw the UML equivalents of the
E-R diagrams Of Figures
6.8c,6.9,6.17,6.72,And 6.20.
7/11/2016 30Prepared By- Shimul & Hirok,CSE,MBSTU
31. Needed Figure of Problem 6 And Its
Solution Given…………………….
7/11/2016 31Prepared By- Shimul & Hirok,CSE,MBSTU