We can solve all assignments of AUS, UK, Canada, Ireland, Germany, New Zealand and USA universities.
Contact us for the following services.
1- Thesis writing
2- Any type of Assignment writing
3- Exams
4- Tests
5- Software engineering
6- Dissertation
7- Reaserch paper
8-Term paper
9- Software and Web developments


Join this👇👇 https://t.me/assignment_project_usa
https://t.me/assignment_project_usa
https://t.me/assignment_project_usa

https://idfcfirstbankcareers.phenompro.com/in/en/job/132960/Associate-Manager-Acquisition-CASA-North


Apply fast instant exam link ✅🧿🧿

Hi guys.. 😅✌️
👉🎯Those want help in Meesho, Infosys, HCL, IBM ,Cognizant,Revature Amazon ,DELOITTE, HCL,  Accenture, nd any placement exams,(onn & OFF campus). Capgemini, Accenture , internal exams nd any company internal exams contact us


100 percent selected 🎯


👉And any certifications(Google, Microsoft, AWS, Pl 300, Pl 400, etc) help contact us 100 percent pass.✅👨‍💻


For more info please contact us

Link : @Coding_000❤️👨‍💻

👉All Offcampus Links join
👉👉@Offcampus_000 ✌️😍

Please refer to ur Frd’s ..  🫶🏻❤️

My request to our group family don't trust anyone simply and don't lose money 🙏🥹

Team @Coding_000❤️

Dm @ILOVEU_143✅


For Coding Help or Any Exam Help 😄


💯 Clearance ✅

Check the previous proofs 👆👆

Contact @ILOVEU_143 👨‍💻

Note: it's paid help

💯 Clearance and genuine help😊✌️

Scroll up and check all proofs we helped😁👨‍💻

Share @Coding_000❤️

TECH Mahindra Exam

Round 1 & 2

Help available.👨‍💻

100% Clearance GUARANTEE.✅

Check our past Results. 👇👇

https://t.me/Coding_000/5567?single
https://t.me/Coding_000/5563?single

Contact @ILOVEU_143 ✅

Complete SQL Topics for Data Analysts 😄👇

1. Introduction to SQL:
   - Basic syntax and structure
   - Understanding databases and tables

2. Querying Data:
   - SELECT statement
   - Filtering data using WHERE clause
   - Sorting data with ORDER BY

3. Joins:
   - INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN
   - Combining data from multiple tables

4. Aggregation Functions:
   - GROUP BY
   - Aggregate functions like COUNT, SUM, AVG, MAX, MIN

5. Subqueries:
   - Using subqueries in SELECT, WHERE, and HAVING clauses

6. Data Modification:
   - INSERT, UPDATE, DELETE statements
   - Transactions and Rollback

7. Data Types and Constraints:
   - Understanding various data types (e.g., INT, VARCHAR)
   - Using constraints (e.g., PRIMARY KEY, FOREIGN KEY)

8. Indexes:
   - Creating and managing indexes for performance optimization

9. Views:
   - Creating and using views for simplified querying

10. Stored Procedures and Functions:
    - Writing and executing stored procedures
    - Creating and using functions

11. Normalization:
    - Understanding database normalization concepts

12. Data Import and Export:
    - Importing and exporting data using SQL

13. Window Functions:
    - ROW_NUMBER(), RANK(), DENSE_RANK(), and others

14. Advanced Filtering:
    - Using CASE statements for conditional logic

15. Advanced Join Techniques:
    - Self-joins and other advanced join scenarios

16. Analytical Functions:
    - LAG(), LEAD(), OVER() for advanced analytics

17. Working with Dates and Times:
    - Date and time functions and formatting

18. Performance Tuning:
    - Query optimization strategies

19. Security:
    - Understanding SQL injection and best practices for security

20. Handling NULL Values:
    - Dealing with NULL values in queries


Since SQL is one of the most essential skill for data analysts, I have decided to teach each topic daily in this channel for free. Like this post if you want me to continue this SQL series 👍♥️


Please go through this, this are the only topic you needs to cover

SQL LEARNING PART-1

Complete SQL Topics for Data Analysis

https://t.me/codingwithharry 👨‍💻❤️

Let's start with the first topic:

📌1. Introduction to SQL:
SQL (Structured Query Language) is a programming language designed for managing and querying relational databases. It provides a standardized way to interact with databases. The basic structure of an SQL query involves:

SELECT column1, column2 FROM table_name WHERE condition;
- `SELECT: Specifies the columns to retrieve.


- FROM: Specifies the table from which to retrieve the data.
- WHERE: Filters the rows based on a condition.

Example:
``sql
SELECT first_name, last_name FROM employees WHERE department = 'IT';

This query retrieves the first name and last name of employees working in the IT department.

Hope it helps :)

SQL Learning Series Part-2

Complete SQL Topics for Data Analysis

https://t.me/codingwithharry

Querying Data

Now that we understand the basic structure, let's delve into querying data with more detail.

#### SELECT Statement:
The SELECT statement retrieves data from one or more tables. You can select specific columns or use * to select all columns.

-- Selecting specific columns
SELECT column1, column2 FROM table_name;

-- Selecting all columns
SELECT * FROM table_name;
#### Filtering Data with WHERE:
The WHERE clause filters rows based on a specified condition.

SELECT column1, column2 FROM table_name WHERE condition;
Example:
SELECT product_name, price FROM products WHERE category = 'Electronics';
This query retrieves the product names and prices for items in the 'Electronics' category.

#### Sorting Data with ORDER BY:
The ORDER BY clause sorts the result set based on one or more columns.

SELECT column1, column2 FROM table_name ORDER BY column1 [ASC|DESC];
Example:
SELECT product_name, price FROM products ORDER BY price DESC;
This query sorts products by price in descending order.

Understanding these fundamentals is crucial for effective data retrieval.


Enjoy your learning❤️✅

Share our channel to ur frds ❤️✌️

SQL Learning Series Part-3

Complete SQL Topics for Data Analysis

https://t.me/codingwithharry 👨‍💻✅

Today, we will learn about Joins in more detail.

Joins allow you to combine rows from two or more tables based on related columns. There are several types of joins:

#### INNER JOIN:
Returns rows when there is a match in both tables.

SELECT column1, column2 FROM table1 INNER JOIN table2 ON table1.column = table2.column;
#### LEFT JOIN (or LEFT OUTER JOIN):

Returns all rows from the left table and matching rows from the right table.

SELECT column1, column2 FROM table1 LEFT JOIN table2 ON table1.column = table2.column;
#### RIGHT JOIN (or RIGHT OUTER JOIN):

Returns all rows from the right table and matching rows from the left table.

SELECT column1, column2 FROM table1 RIGHT JOIN table2 ON table1.column = table2.column;
#### FULL JOIN (or FULL OUTER JOIN):

Returns all rows when there is a match in either table.

SELECT column1, column2 FROM table1 FULL JOIN table2 ON table1.column = table2.column;
Joins are powerful for combining data from different sources. 

Kindly go through this and share your response 👍

SQL LEARNING SERIES PART-4

Complete SQL Topics for Data Analysis

https://t.me/codingwithharry 👨‍💻✅

Today, we will learn about Aggregate Functions

Aggregation functions perform calculations on sets of values and return a single result. Common aggregation functions include:

#### COUNT():
Counts the number of rows in a result set.

SELECT COUNT(column) FROM table;
#### SUM():

Calculates the sum of values in a column.

SELECT SUM(column) FROM table;
#### AVG():
Calculates the average value of a numeric column.

SELECT AVG(column) FROM table;
#### MAX():
Returns the maximum value in a column.

SELECT MAX(column) FROM table;
#### MIN():
Returns the minimum value in a column.

SELECT MIN(column) FROM table;

```sql
Example:```
```sql

SELECT COUNT(order_id), AVG(total_amount) FROM orders WHERE customer_id = 123;
This query counts the number of orders and calculates the average total amount for a specific customer.`


Understanding aggregation is crucial for summarizing and analyzing data.


Please go through this 👍

SQL Learning Series Part 5: Mastering Subqueries

Delve deeper into SQL's capabilities with Subqueries, a powerful tool for seamless integration of query results. Explore various types to elevate your data analysis skills:

1. Subquery in SELECT:
Retrieve a single value using a subquery. Perfect for incorporating dynamic data into your result set.

SELECT column1, (SELECT column2 FROM table2 WHERE condition) AS subquery_result FROM table1;

2. Subquery in WHERE:
Filter results based on the outcome of a subquery. Tailor your queries dynamically for precise data retrieval.

SELECT column1 FROM table1 WHERE column2 = (SELECT column3 FROM table2 WHERE condition);

3. Subquery in HAVING:
Refine aggregated results with a subquery. Apply conditions to aggregated data for more nuanced insights.

SELECT column1, COUNT(column2) FROM table1 GROUP BY column1 HAVING COUNT(column2) > (SELECT threshold FROM settings);

4. Correlated Subqueries:
Create dynamic relationships between the inner and outer queries, allowing for more contextual and relevant results.

SELECT column1, column2 FROM table1 WHERE column2 > (SELECT AVG(column2) FROM table1 WHERE table1.column1 = column1);

5. EXISTS and NOT EXISTS:
Determine the existence of rows satisfying a condition, offering a powerful way to check for data presence.

SELECT column1 FROM table1 WHERE EXISTS (SELECT 1 FROM table2 WHERE table2.column1 = table1.column1);

Subqueries unlock a new dimension in SQL, providing solutions for complex data analysis scenarios. Elevate your queries with these advanced techniques and empower your database exploration.

Hope this was helpful..

SQL Learning Series Part 6: Data Modification Magic ✨🔧

Complete SQL topics for Data Analysis

https://t.me/codingwithharry 😍✌️

Dive into the world of SQL data modification, where you'll master the art of shaping and refining your database. Explore key topics and commands for effective data manipulation:

🔧 Section 1: INSERT Statements
   - Learn the syntax and usage of INSERT statements to add new records.
   - Explore ways to insert data into specific columns for precise data entry.

 

   INSERT INTO table_name (column1, column2) VALUES (value1, value2);
   

🔧 Section 2: UPDATE Statements
   - Understand how to modify existing records using UPDATE statements.
   - Explore the power of WHERE clause for targeted updates.

 

   UPDATE table_name SET column1 = value1 WHERE condition;
   

🔧 Section 3: DELETE Statements
   - Delve into the DELETE statement for removing records from a table.
   - Explore the use of WHERE clause to delete specific records.

 

   DELETE FROM table_name WHERE condition;
   

🔧 Section 4: Transactions and Rollback
   - Grasp the concept of transactions for managing a series of SQL commands.
   - Learn the importance of COMMIT and ROLLBACK for data consistency.

 

   BEGIN TRANSACTION;
   -- SQL Statements
   COMMIT;
   -- or
   ROLLBACK;
   

Happy modifying! 🚀

SQL Learning Series Part 7: Data Types and Constraints 🛠️🔗

Complete sql  topic for data analysis

https://t.me/CODINGWITHHARRY ✅
🔗 Section 1: Data Types Exploration
   - Uncover the diverse world of data types (e.g., INT, VARCHAR, DATE).
   - Understand the significance of choosing the right data type for each column.

 

   CREATE TABLE example_table (
       column1 INT,
       column2 VARCHAR(50),
       column3 DATE
   );
   

🔗 Section 2: Constraint Implementation
   - Master the art of using constraints for data integrity.
   - Explore PRIMARY KEY and FOREIGN KEY constraints for relational structure.

 

   CREATE TABLE employees (
       employee_id INT PRIMARY KEY,
       department_id INT,
       FOREIGN KEY (department_id) REFERENCES departments(department_id)
   );
   

🔗 Section 3: NOT NULL Constraint
   - Implement the NOT NULL constraint to ensure data completeness.
   - Ensure that specific columns always have values.

 

   CREATE TABLE example_table (
       column1 INT NOT NULL,
       column2 VARCHAR(50) NOT NULL
   );
   

🔗 Section 4: UNIQUE Constraint
   - Enforce uniqueness within a column using the UNIQUE constraint.
   - Ensure that no duplicate values exist in the specified column.

 

   CREATE TABLE example_table (
       column1 INT UNIQUE,
       column2 VARCHAR(50) UNIQUE
   );
   

🔗 Section 5: Check Constraint
   - Add a Check Constraint to enforce specific conditions on column values.
   - Control the range or format of allowed values.

 

   CREATE TABLE example_table (
       column1 INT,
       column2 VARCHAR(50),
       CHECK (column1 > 0 AND column1 < 100)
   );
   

shaping a resilient foundation for your SQL database.

Happy structuring! 🏗️