What is difference between “Clustered Index” and “Non Clustered Index”?
1. A Clustered Index physically stores the data of the table in the order of the keys values and the data is resorted every time whenever a new value is inserted or a value is updated in the column on which it is defined, whereas a non-clustered index creates a separate list of key values (or creates a table of pointers) that points towards the location of the data in the data pages.
2. A Clustered Index requires no separate storage than the table storage. It forces the rows to be stored sorted on the index key whereas a non-clustered index requires separate storage than the table storage to store the index information.
3. A table with a Clustered Index is called a Clustered Table. Its rows are stored in a B-Tree structure sorted whereas a table without any clustered indexes is called a non-clustered table. Its rows are stored in a heap structure unsorted.
4. The default index is created as part of the primary key column as a Clustered Index.
5. In a Clustered Index, the leaf node contains the actual data whereas in a non-clustered index, the leaf node contains the pointer to the data rows of the table.
6. A Clustered Index always has an Index Id of 1 whereas non-clustered indexes have Index Ids > 1.
7. A Table can have only 1 Clustered Index whereas prior to SQL Server 2008 only 249 non-clustered indexes can be created. With SQL Server 2008 and above 999 non-clustered indexes can be created.
8. A Primary Key constraint creates a Clustered Index by default whereas A Unique Key constraint creates a non-clustered index by default.
1. A Clustered Index physically stores the data of the table in the order of the keys values and the data is resorted every time whenever a new value is inserted or a value is updated in the column on which it is defined, whereas a non-clustered index creates a separate list of key values (or creates a table of pointers) that points towards the location of the data in the data pages.
2. A Clustered Index requires no separate storage than the table storage. It forces the rows to be stored sorted on the index key whereas a non-clustered index requires separate storage than the table storage to store the index information.
3. A table with a Clustered Index is called a Clustered Table. Its rows are stored in a B-Tree structure sorted whereas a table without any clustered indexes is called a non-clustered table. Its rows are stored in a heap structure unsorted.
4. The default index is created as part of the primary key column as a Clustered Index.
5. In a Clustered Index, the leaf node contains the actual data whereas in a non-clustered index, the leaf node contains the pointer to the data rows of the table.
6. A Clustered Index always has an Index Id of 1 whereas non-clustered indexes have Index Ids > 1.
7. A Table can have only 1 Clustered Index whereas prior to SQL Server 2008 only 249 non-clustered indexes can be created. With SQL Server 2008 and above 999 non-clustered indexes can be created.
8. A Primary Key constraint creates a Clustered Index by default whereas A Unique Key constraint creates a non-clustered index by default.
What is the difference between the “DELETE” and “TRUNCATE” commands?
1. The DELETE command is used to remove rows from a table based on a WHERE condition whereas TRUNCATE removes all rows from a table.
2. So we can use a where clause with DELETE to filter and delete specific records whereas we cannot use a Where clause with TRUNCATE.
3. DELETE is executed using a row lock, each row in the table is locked for deletion whereas TRUNCATE is executed using a table lock and the entire table is locked for removal of all records.
4. DELETE is a DML command whereas TRUNCATE is a DDL command.
5. DELETE retains the identity of the column value whereas in TRUNCATE, the Identify column is reset to its seed value if the table contains any identity column.
6. To use Delete you need DELETE permission on the table whereas to use Truncate on a table you need at least ALTER permission on the table.
7. DELETE uses more transaction space than the TRUNCATE statement whereas Truncate uses less transaction space than DELETE statement.
8. DELETE can be used with indexed views whereas TRUNCATE cannot be used with indexed views.
9. The DELETE statement removes rows one at a time and records an entry in the transaction log for each deleted row whereas TRUNCATE TABLE removes the data by deallocating the data pages used to store the table data and records only the page deallocations in the transaction log.
10. Delete activates a trigger because the operation is logged individually whereas TRUNCATE TABLE can't activate a trigger because the operation does not log individual row deletions.
1. The DELETE command is used to remove rows from a table based on a WHERE condition whereas TRUNCATE removes all rows from a table.
2. So we can use a where clause with DELETE to filter and delete specific records whereas we cannot use a Where clause with TRUNCATE.
3. DELETE is executed using a row lock, each row in the table is locked for deletion whereas TRUNCATE is executed using a table lock and the entire table is locked for removal of all records.
4. DELETE is a DML command whereas TRUNCATE is a DDL command.
5. DELETE retains the identity of the column value whereas in TRUNCATE, the Identify column is reset to its seed value if the table contains any identity column.
6. To use Delete you need DELETE permission on the table whereas to use Truncate on a table you need at least ALTER permission on the table.
7. DELETE uses more transaction space than the TRUNCATE statement whereas Truncate uses less transaction space than DELETE statement.
8. DELETE can be used with indexed views whereas TRUNCATE cannot be used with indexed views.
9. The DELETE statement removes rows one at a time and records an entry in the transaction log for each deleted row whereas TRUNCATE TABLE removes the data by deallocating the data pages used to store the table data and records only the page deallocations in the transaction log.
10. Delete activates a trigger because the operation is logged individually whereas TRUNCATE TABLE can't activate a trigger because the operation does not log individual row deletions.
What is the difference between the “WHERE” clause and the “HAVING” clause?
1. WHERE clause can be used with a Select, Update and Delete Statement Clause but the HAVING clause can be used only with a Select statement.
2. We can't use an aggregate function in the WHERE clause unless it is in a sub-query contained in a HAVING clause whereas we can use an aggregate function in the HAVING clause. We can use a column name in the HAVING clause but the column must be contained in the group by clause.
3. WHERE is used before the GROUP BY clause whereas a HAVING clause is used to impose a condition on the GROUP Function and is used after the GROUP BY clause in the query.
4. A WHERE clause applies to each and every row whereas a HAVING clause applies to summarized rows (summarized with GROUP BY).
5. In the WHERE clause the data that is fetched from memory depending on a condition whereas in HAVING the completed data is first fetched and then separated depending on the condition.
1. WHERE clause can be used with a Select, Update and Delete Statement Clause but the HAVING clause can be used only with a Select statement.
2. We can't use an aggregate function in the WHERE clause unless it is in a sub-query contained in a HAVING clause whereas we can use an aggregate function in the HAVING clause. We can use a column name in the HAVING clause but the column must be contained in the group by clause.
3. WHERE is used before the GROUP BY clause whereas a HAVING clause is used to impose a condition on the GROUP Function and is used after the GROUP BY clause in the query.
4. A WHERE clause applies to each and every row whereas a HAVING clause applies to summarized rows (summarized with GROUP BY).
5. In the WHERE clause the data that is fetched from memory depending on a condition whereas in HAVING the completed data is first fetched and then separated depending on the condition.
What is the difference between “Primary Key” and “Unique Key”?
1. We can have only one Primary Key in a table whereas we can have more than one Unique Key in a table.
2. The Primary Key cannot have a NULL value whereas a Unique Key may have only one null value.
3. By default, a Primary Key is a Clustered Index whereas by default, a Unique Key is a unique non-clustered index.
4. A Primary Key supports an Auto Increment value whereas a Unique Key doesn't support an Auto Increment value.
1. We can have only one Primary Key in a table whereas we can have more than one Unique Key in a table.
2. The Primary Key cannot have a NULL value whereas a Unique Key may have only one null value.
3. By default, a Primary Key is a Clustered Index whereas by default, a Unique Key is a unique non-clustered index.
4. A Primary Key supports an Auto Increment value whereas a Unique Key doesn't support an Auto Increment value.
What is the difference between a “Local Temporary Table” and “Global Temporary Table”?
1. A Local Temporary Table is created by giving it a prefix of # whereas a Global Temporary Table is created by giving it a prefix of ##.
2. A Local Temporary Table cannot be shared among multiple users whereas a Global Temporary Table can be shared among multiple users.
3. A Local Temporary Table is only available to the current DB connection for the current user and are cleared when the connection is closed whereas a Global Temporary Table is available to any connection once created. They are cleared when the last connection is closed.
1. A Local Temporary Table is created by giving it a prefix of # whereas a Global Temporary Table is created by giving it a prefix of ##.
2. A Local Temporary Table cannot be shared among multiple users whereas a Global Temporary Table can be shared among multiple users.
3. A Local Temporary Table is only available to the current DB connection for the current user and are cleared when the connection is closed whereas a Global Temporary Table is available to any connection once created. They are cleared when the last connection is closed.
SQL Interview Questions Everyone Should Know
Questions are categorized into 20 groups based on their similarity as following:
1-Get duplicate records
2-Delete duplicate records
3-Get 1 to 100 Numbers
4-Get second highest salary
5-Get N'th highest salary
6-Alternative for TOP clause
7-Get Between and Greater than records
8-Get N last records
9-Department wise records
10-Create and copied table/data from another table
11-Get odd/even id records
12-Get max and min salaries
13-Get records with the same salary
14-Get 50% records
15-Get manager name for employees
16-Get employee name starting/ending with
17-Use of like
18-Group concept
19-Date related concept
20-Some random related and other concepts
Questions are categorized into 20 groups based on their similarity as following:
1-Get duplicate records
2-Delete duplicate records
3-Get 1 to 100 Numbers
4-Get second highest salary
5-Get N'th highest salary
6-Alternative for TOP clause
7-Get Between and Greater than records
8-Get N last records
9-Department wise records
10-Create and copied table/data from another table
11-Get odd/even id records
12-Get max and min salaries
13-Get records with the same salary
14-Get 50% records
15-Get manager name for employees
16-Get employee name starting/ending with
17-Use of like
18-Group concept
19-Date related concept
20-Some random related and other concepts
Interview Question: “Where do you see yourself in 5 years?”
Interviewers ask this question not to reject you immediately but to understand:
✅ Your career ambitions
✅ Your fit with the company culture
✅ Your drive and self-awareness
✅ Your decision making
Here’s how you can respond ⬇️
💡Sample answer:
In 5 years, I see myself in a leadership role within this company, managing a team, and driving key initiatives. I'm passionate about the work we do here, and my goal is to become an expert in my field, known for delivering exceptional results. What excites me the most is the growth potential within this organization. I've seen several employees advance to influential positions, and I'm eager to follow in their footsteps. With my dedication, your mentorship, and the shared values of this company, I am confident in my ability to contribute to its ongoing success.
Interviewers ask this question not to reject you immediately but to understand:
✅ Your career ambitions
✅ Your fit with the company culture
✅ Your drive and self-awareness
✅ Your decision making
Here’s how you can respond ⬇️
💡Sample answer:
In 5 years, I see myself in a leadership role within this company, managing a team, and driving key initiatives. I'm passionate about the work we do here, and my goal is to become an expert in my field, known for delivering exceptional results. What excites me the most is the growth potential within this organization. I've seen several employees advance to influential positions, and I'm eager to follow in their footsteps. With my dedication, your mentorship, and the shared values of this company, I am confident in my ability to contribute to its ongoing success.
👍1
How to respond when asked about your weaknesses during an interview?
💡Sample answer: ⬇️
I struggled with time management and procrastination in my last role because I was taking on too many tasks at once. To improve, I started using a daily planner to schedule priorities and block off time for deep work. This helps me stay focused and meet deadlines. Being proactive about managing my time has really helped me become more productive. 💪
💡Sample answer: ⬇️
I struggled with time management and procrastination in my last role because I was taking on too many tasks at once. To improve, I started using a daily planner to schedule priorities and block off time for deep work. This helps me stay focused and meet deadlines. Being proactive about managing my time has really helped me become more productive. 💪
4 LIFE - CHANGING IDEAS THAT WE SHOULD ALL KNOW ABOUT ⬇️
1. Murphy's Law: Anything that can go wrong, will go wrong.
2. Kridlin's Law: If you write a problem clearly and specifically, you have solved half of it.
3. Wilson's Law: If you prioritize knowledge and intelligence, money will continue to come.
4. Falkland's Law: If you don’t have to make a decision about something, then don’t decide.
P.S. What principles guide your approach to life and business?
Let me know in the comments!
1. Murphy's Law: Anything that can go wrong, will go wrong.
2. Kridlin's Law: If you write a problem clearly and specifically, you have solved half of it.
3. Wilson's Law: If you prioritize knowledge and intelligence, money will continue to come.
4. Falkland's Law: If you don’t have to make a decision about something, then don’t decide.
P.S. What principles guide your approach to life and business?
Let me know in the comments!
⛳️SQL CLAUSES:
SQL clause helps us to retrieve a set or bundles of records from the table.
SQL clause helps us to specify a condition on the columns or the records of a table.
There are generally five kinds of SQL Clauses . They are listed as follows:
1-WHERE Clause
2-ORDER BY clause
3-HAVING Clause
4-TOP Clause
5-GROUP BY Clause
1. SQL WHERE Clause:
we use the SQL SELECT statement to select data from a table in the database. Here, the WHERE clause allows filtering certain records that exactly match a specified condition. Thus, it helps us to fetch only the necessary data from the database that satisfies the given expressional conditions. The WHERE clause is used with SELECT statement as well as with UPDATE, DELETE type statements and aggregate functions to restrict the no. of records to be retrieved by the table. We can also use logical or comparison operators such as LIKE,<,>,=, etc. with WHERE clause to fulfill certain conditions.
Query:
SELECT BookName, Price, Lang From Books WHERE CatID >1;
2. SQL ORDER BY Clause:
The ORDER BY clause is used in SQL for sorting records. It is used to arrange the result set either in ascending or descending order. When we query using SELECT statement the result is not in an ordered form. Hence, the result rows can be sorted when we combine the SELECT statement with the ORDER BY clause.
Query:
SELECT BookName, Price From Books ORDER BY Price ASC;
3. SQL GROUP BY Clause:
The GROUP BY clause is used to group rows that have the same values in the result set. Like if we find the names of books from the table grouped by CatID.
Query:
SELECT COUNT(BookName), CatID From Books GROUP BY CatID;
This clause is generally used with aggregate functions that allow grouping the query result rows by multiple columns. The aggregate functions are COUNT, MAX, MIN, SUM, AVG, etc.
4. SQL HAVING Clause:
Actually, this clause is introduced to apply functions in the query with the WHERE clause. In SQL, the HAVING clause was added because the WHERE clause could not be applied with aggregate functions.
Query:
SELECT COUNT (CatID), Lang From Books GROUP BY Lang HAVING COUNT(CATID) <3;
5. SQL TOP Clause:
The TOP clause is used to determine the number of record rows to be shown in the result. This TOP clause is used with SELECT statement specially implemented on large tables with many records. But the clause is not supported in many database systems, like MySQL supports the LIMIT clause to select limited no. of rows and in Oracle ROWNUM is used.
Query:
SELECT TOP 3 * FROM Books;
SELECT * FROM Books LIMIT 3;
SELECT * FROM Books WHERE ROWNUM <= 3;
SQL clause helps us to retrieve a set or bundles of records from the table.
SQL clause helps us to specify a condition on the columns or the records of a table.
There are generally five kinds of SQL Clauses . They are listed as follows:
1-WHERE Clause
2-ORDER BY clause
3-HAVING Clause
4-TOP Clause
5-GROUP BY Clause
1. SQL WHERE Clause:
we use the SQL SELECT statement to select data from a table in the database. Here, the WHERE clause allows filtering certain records that exactly match a specified condition. Thus, it helps us to fetch only the necessary data from the database that satisfies the given expressional conditions. The WHERE clause is used with SELECT statement as well as with UPDATE, DELETE type statements and aggregate functions to restrict the no. of records to be retrieved by the table. We can also use logical or comparison operators such as LIKE,<,>,=, etc. with WHERE clause to fulfill certain conditions.
Query:
SELECT BookName, Price, Lang From Books WHERE CatID >1;
2. SQL ORDER BY Clause:
The ORDER BY clause is used in SQL for sorting records. It is used to arrange the result set either in ascending or descending order. When we query using SELECT statement the result is not in an ordered form. Hence, the result rows can be sorted when we combine the SELECT statement with the ORDER BY clause.
Query:
SELECT BookName, Price From Books ORDER BY Price ASC;
3. SQL GROUP BY Clause:
The GROUP BY clause is used to group rows that have the same values in the result set. Like if we find the names of books from the table grouped by CatID.
Query:
SELECT COUNT(BookName), CatID From Books GROUP BY CatID;
This clause is generally used with aggregate functions that allow grouping the query result rows by multiple columns. The aggregate functions are COUNT, MAX, MIN, SUM, AVG, etc.
4. SQL HAVING Clause:
Actually, this clause is introduced to apply functions in the query with the WHERE clause. In SQL, the HAVING clause was added because the WHERE clause could not be applied with aggregate functions.
Query:
SELECT COUNT (CatID), Lang From Books GROUP BY Lang HAVING COUNT(CATID) <3;
5. SQL TOP Clause:
The TOP clause is used to determine the number of record rows to be shown in the result. This TOP clause is used with SELECT statement specially implemented on large tables with many records. But the clause is not supported in many database systems, like MySQL supports the LIMIT clause to select limited no. of rows and in Oracle ROWNUM is used.
Query:
SELECT TOP 3 * FROM Books;
SELECT * FROM Books LIMIT 3;
SELECT * FROM Books WHERE ROWNUM <= 3;
👍1
🔥𝐒𝐎𝐑𝐓𝐈𝐍𝐆 𝐀𝐋𝐆𝐎𝐑𝐈𝐓𝐇𝐌𝐒 𝐂𝐎𝐌𝐏𝐋𝐄𝐗𝐈𝐓𝐘 𝐂𝐇𝐄𝐀𝐓𝐒𝐇𝐄𝐄𝐓🚀
Excited to share this handy cheatsheet on Sorting Algorithms' Time Complexity! 🔍 Whether you're a coding enthusiast or a tech professional, understanding sorting algorithms' efficiency is key.⚡️ Here's a quick reference guide to help you navigate through different algorithms and their time complexitie.🙌
📝 Here's a detailed cheatsheet to help you grasp the time complexities of various sorting algorithms:
📌 𝗕𝘂𝗯𝗯𝗹𝗲 𝗦𝗼𝗿𝘁 🫧
🔹Best Case: O(n)
🔹Average Case: O(n^2)
🔹Worst Case: O(n^2)
📌 𝗜𝗻𝘀𝗲𝗿𝘁𝗶𝗼𝗻 𝗦𝗼𝗿𝘁 💥
🔹Best Case: O(n)
🔹Average Case: O(n^2)
🔹Worst Case: O(n^2)
📌 𝗦𝗲𝗹𝗲𝗰𝘁𝗶𝗼𝗻 𝗦𝗼𝗿𝘁 ✅
🔹Best Case: O(n^2)
🔹Average Case: O(n^2)
🔹Worst Case: O(n^2)
📌 𝗠𝗲𝗿𝗴𝗲 𝗦𝗼𝗿𝘁 🤝
🔹Best Case: O(n log n)
🔹Average Case: O(n log n)
🔹Worst Case: O(n log n)
📌 𝗤𝘂𝗶𝗰𝗸 𝗦𝗼𝗿𝘁 ⚡️
🔹Best Case: O(n log n)
🔹Average Case: O(n log n)
🔹Worst Case: O(n^2)
📌 𝗛𝗲𝗮𝗽 𝗦𝗼𝗿𝘁 📚
🔹Best Case: O(n log n)
🔹Average Case: O(n log n)
🔹Worst Case: O(n log n)
📌 𝗥𝗮𝗱𝗶𝘅 𝗦𝗼𝗿𝘁 💫
🔹Best Case: O(nk)
🔹Average Case: O(nk)
🔹Worst Case: O(nk)
📌 𝗖𝗼𝘂𝗻𝘁𝗶𝗻𝗴 𝗦𝗼𝗿𝘁 📊
🔹Best Case: O(n + k)
🔹Average Case: O(n + k)
🔹Worst Case: O(n + k)
📌 𝗕𝘂𝗰𝗸𝗲𝘁 𝗦𝗼𝗿𝘁 🪣
🔹Best Case: O(n + k)
🔹Average Case: O(n + k)
🔹Worst Case: O(n^2)
📌 𝗖𝗼𝘂𝗻𝘁𝗶𝗻𝗴 𝗦𝗼𝗿𝘁 📊
🔹Best Case: O(n + k)
🔹Average Case: O(n + k)
🔹Worst Case: O(n + k)
📚Remember, each algorithm has its strengths and weaknesses. Depending on the size of your data and the specific use case, you can choose the most suitable sorting algorithm to ensure efficient code execution.💫
Excited to share this handy cheatsheet on Sorting Algorithms' Time Complexity! 🔍 Whether you're a coding enthusiast or a tech professional, understanding sorting algorithms' efficiency is key.⚡️ Here's a quick reference guide to help you navigate through different algorithms and their time complexitie.🙌
📝 Here's a detailed cheatsheet to help you grasp the time complexities of various sorting algorithms:
📌 𝗕𝘂𝗯𝗯𝗹𝗲 𝗦𝗼𝗿𝘁 🫧
🔹Best Case: O(n)
🔹Average Case: O(n^2)
🔹Worst Case: O(n^2)
📌 𝗜𝗻𝘀𝗲𝗿𝘁𝗶𝗼𝗻 𝗦𝗼𝗿𝘁 💥
🔹Best Case: O(n)
🔹Average Case: O(n^2)
🔹Worst Case: O(n^2)
📌 𝗦𝗲𝗹𝗲𝗰𝘁𝗶𝗼𝗻 𝗦𝗼𝗿𝘁 ✅
🔹Best Case: O(n^2)
🔹Average Case: O(n^2)
🔹Worst Case: O(n^2)
📌 𝗠𝗲𝗿𝗴𝗲 𝗦𝗼𝗿𝘁 🤝
🔹Best Case: O(n log n)
🔹Average Case: O(n log n)
🔹Worst Case: O(n log n)
📌 𝗤𝘂𝗶𝗰𝗸 𝗦𝗼𝗿𝘁 ⚡️
🔹Best Case: O(n log n)
🔹Average Case: O(n log n)
🔹Worst Case: O(n^2)
📌 𝗛𝗲𝗮𝗽 𝗦𝗼𝗿𝘁 📚
🔹Best Case: O(n log n)
🔹Average Case: O(n log n)
🔹Worst Case: O(n log n)
📌 𝗥𝗮𝗱𝗶𝘅 𝗦𝗼𝗿𝘁 💫
🔹Best Case: O(nk)
🔹Average Case: O(nk)
🔹Worst Case: O(nk)
📌 𝗖𝗼𝘂𝗻𝘁𝗶𝗻𝗴 𝗦𝗼𝗿𝘁 📊
🔹Best Case: O(n + k)
🔹Average Case: O(n + k)
🔹Worst Case: O(n + k)
📌 𝗕𝘂𝗰𝗸𝗲𝘁 𝗦𝗼𝗿𝘁 🪣
🔹Best Case: O(n + k)
🔹Average Case: O(n + k)
🔹Worst Case: O(n^2)
📌 𝗖𝗼𝘂𝗻𝘁𝗶𝗻𝗴 𝗦𝗼𝗿𝘁 📊
🔹Best Case: O(n + k)
🔹Average Case: O(n + k)
🔹Worst Case: O(n + k)
📚Remember, each algorithm has its strengths and weaknesses. Depending on the size of your data and the specific use case, you can choose the most suitable sorting algorithm to ensure efficient code execution.💫
👉What is Database Management System?
Data:
"Collection of quantitative and qualitative variables is known as data".
Type of Data:
1-Raw Data
2-Processed data(Information)
👉What is DBMS?
DBMS consist of two parts
1-Data base
2-Management System.
Database is a collection of interrelated files and the basic management operations are
Searching,
Addition,
Deletion,
Updation,
A DBMS consist of collection of related data and a set of programs to access and manipulate those data.
"The database management system is a general purpose software system that facilitates the process of defining, constructing, manipulating and sharing database among, various user and application".
The primary objective of DBMS is to provides an environment that is convenient and efficient to use in retrieving and storing data in database. The DBMS should use minimum set of computing resources to provides maximum throughout.
Basic terminology of DBMS .
🥇Field:
"fields are in the form of rows".
🥇Records:
"Data organized in meaningful way to known as Records".
🥇File:
"Collection of similar records is known as file".
🥇Database:
"collection of interrelated files is called database".
following are basic facilities provided by DBMS.
⚡creation,
⚡insertion,
⚡deletion,
⚡modification and
⚡retrieval,
⚡protecting of data and ⚡maintaining integrity,
⚡report generation,
⚡mathematical operation.
Subscribe my channel
👉@CoderBaba
https://www.youtube.com/coderbaba
Data:
"Collection of quantitative and qualitative variables is known as data".
Type of Data:
1-Raw Data
2-Processed data(Information)
👉What is DBMS?
DBMS consist of two parts
1-Data base
2-Management System.
Database is a collection of interrelated files and the basic management operations are
Searching,
Addition,
Deletion,
Updation,
A DBMS consist of collection of related data and a set of programs to access and manipulate those data.
"The database management system is a general purpose software system that facilitates the process of defining, constructing, manipulating and sharing database among, various user and application".
The primary objective of DBMS is to provides an environment that is convenient and efficient to use in retrieving and storing data in database. The DBMS should use minimum set of computing resources to provides maximum throughout.
Basic terminology of DBMS .
🥇Field:
"fields are in the form of rows".
🥇Records:
"Data organized in meaningful way to known as Records".
🥇File:
"Collection of similar records is known as file".
🥇Database:
"collection of interrelated files is called database".
following are basic facilities provided by DBMS.
⚡creation,
⚡insertion,
⚡deletion,
⚡modification and
⚡retrieval,
⚡protecting of data and ⚡maintaining integrity,
⚡report generation,
⚡mathematical operation.
Subscribe my channel
👉@CoderBaba
https://www.youtube.com/coderbaba