SQL for Data Analysis


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Категория: Технологии


Find top SQL resources from global universities, cool projects, and learning materials for data analytics.
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не указан, Английский
Категория
Технологии
Статистика
Фильтр публикаций


Complete 14-day roadmap to learn SQL learning:

Day 1: Introduction to Databases
- Understand the concept of databases and their importance.
- Learn about relational databases and SQL.
- Explore the basic structure of SQL queries.

Day 2: Basic SQL Syntax
- Learn SQL syntax: statements, clauses, and keywords.
- Understand the SELECT statement for retrieving data.
- Practice writing basic SELECT queries with conditions and filters.

Day 3: Retrieving Data from Multiple Tables
- Learn about joins: INNER JOIN, LEFT JOIN, RIGHT JOIN.
- Understand how to retrieve data from multiple tables using joins.
- Practice writing queries involving multiple tables.

Day 4: Aggregate Functions
- Learn about aggregate functions: COUNT, SUM, AVG, MIN, MAX.
- Understand how to use aggregate functions to perform calculations on data.
- Practice writing queries with aggregate functions.

Day 5: Subqueries
- Learn about subqueries and their role in SQL.
- Understand how to use subqueries in SELECT, WHERE, and FROM clauses.
- Practice writing queries with subqueries.

Day 6: Data Manipulation Language (DML)
- Learn about DML commands: INSERT, UPDATE, DELETE.
- Understand how to add, modify, and delete data in a database.
- Practice writing DML statements.

Day 7: Data Definition Language (DDL)
- Learn about DDL commands: CREATE TABLE, ALTER TABLE, DROP TABLE.
- Understand constraints: PRIMARY KEY, FOREIGN KEY, UNIQUE, NOT NULL.
- Practice designing database schemas and creating tables.

Day 8: Data Control Language (DCL)
- Learn about DCL commands: GRANT, REVOKE for managing user permissions.
- Understand how to control access to database objects.
- Practice granting and revoking permissions.

Day 9: Transactions
- Understand the concept of transactions in SQL.
- Learn about transaction control commands: COMMIT, ROLLBACK.
- Practice managing transactions.

Day 10: Views
- Learn about views and their benefits.
- Understand how to create, modify, and drop views.
- Practice creating views.

Day 11: Indexes
- Learn about indexes and their role in database optimization.
- Understand different types of indexes (e.g., B-tree, hash).
- Practice creating and managing indexes.

Day 12: Optimization Techniques
- Explore optimization techniques such as query tuning and normalization.
- Understand the importance of database design for optimization.
- Practice optimizing SQL queries.

Day 13: Review and Practice
- Review all concepts covered in the previous days.
- Work on sample projects or exercises to reinforce learning.
- Take practice quizzes or tests.

Day 14: Final Review and Projects
- Review all concepts learned throughout the 14 days.
- Work on a final project to apply SQL knowledge.
- Seek out additional resources or tutorials if needed.


Here are some practical SQL syntax examples for each day of your learning journey:

Day 1: Introduction to Databases
- Syntax to select all columns from a table:
   SELECT * FROM table_name;
 
Day 2: Basic SQL Syntax
- Syntax to select specific columns from a table:
   SELECT column1, column2 FROM table_name;
 
Day 3: Retrieving Data from Multiple Tables
- Syntax for INNER JOIN to retrieve data from two tables:
   SELECT orders.order_id, customers.customer_name
  FROM orders
  INNER JOIN customers ON orders.customer_id = customers.customer_id;
 
Day 4: Aggregate Functions
- Syntax for COUNT to count the number of rows in a table:
   SELECT COUNT(*) FROM table_name;
 
Day 5: Subqueries
- Syntax for using a subquery in the WHERE clause:
   SELECT column1, column2
  FROM table_name
  WHERE column1 IN (SELECT column1 FROM another_table WHERE condition);
 
Day 6: Data Manipulation Language (DML)
- Syntax for INSERT to add data into a table:
   INSERT INTO table_name (column1, column2) VALUES (value1, value2);
 
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Here are the SQL interview questions:

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Basic SQL Questions


1.⁠ ⁠What is SQL, and what is its purpose?
2.⁠ ⁠Write a SQL query to retrieve all records from a table.
3.⁠ ⁠How do you select specific columns from a table?
4.⁠ ⁠What is the difference between WHERE and HAVING clauses?
5.⁠ ⁠How do you sort data in ascending/descending order?


SQL Query Questions


1.⁠ ⁠Write a SQL query to retrieve the top 10 records from a table based on a specific column.
2.⁠ ⁠How do you join two tables based on a common column?
3.⁠ ⁠Write a SQL query to retrieve data from multiple tables using subqueries.
4.⁠ ⁠How do you use aggregate functions (SUM, AVG, MAX, MIN)?
5.⁠ ⁠Write a SQL query to retrieve data from a table for a specific date range.


SQL Optimization Questions


1.⁠ ⁠How do you optimize SQL query performance?
2.⁠ ⁠What is indexing, and how does it improve query performance?
3.⁠ ⁠How do you avoid full table scans?
4.⁠ ⁠What is query caching, and how does it work?
5.⁠ ⁠How do you optimize SQL queries for large datasets?


SQL Joins and Subqueries


1.⁠ ⁠Explain the difference between INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOIN.
2.⁠ ⁠Write a SQL query to retrieve data from two tables using a subquery.
3.⁠ ⁠How do you use EXISTS and IN operators in SQL?
4.⁠ ⁠Write a SQL query to retrieve data from multiple tables using a self-join.
5.⁠ ⁠Explain the concept of correlated subqueries.


SQL Data Modeling


1.⁠ ⁠Explain the concept of normalization and denormalization.
2.⁠ ⁠How do you design a database schema for a given application?
3.⁠ ⁠What is data redundancy, and how do you avoid it?
4.⁠ ⁠Explain the concept of primary and foreign keys.
5.⁠ ⁠How do you handle data inconsistencies and anomalies?


SQL Advanced Questions


1.⁠ ⁠Explain the concept of window functions (ROW_NUMBER, RANK, etc.).
2.⁠ ⁠Write a SQL query to retrieve data using Common Table Expressions (CTEs).
3.⁠ ⁠How do you use dynamic SQL?
4.⁠ ⁠Explain the concept of stored procedures and functions.
5.⁠ ⁠Write a SQL query to retrieve data using pivot tables.


SQL Scenario-Based Questions


1.⁠ ⁠You have two tables, Orders and Customers. Write a SQL query to retrieve all orders for customers from a specific region.
2.⁠ ⁠You have a table with duplicate records. Write a SQL query to remove duplicates.
3.⁠ ⁠You have a table with missing values. Write a SQL query to replace missing values with a default value.
4.⁠ ⁠You have a table with data in an incorrect format. Write a SQL query to correct the format.
5.⁠ ⁠You have two tables with different data types for a common column. Write a SQL query to join the tables.


SQL Behavioral Questions


1.⁠ ⁠Can you explain a time when you optimized a slow-running SQL query?
2.⁠ ⁠How do you handle database errors and exceptions?
3.⁠ ⁠Can you describe a complex SQL query you wrote and why?
4.⁠ ⁠How do you stay up-to-date with new SQL features and best practices?
5.⁠ ⁠Can you walk me through your process for troubleshooting SQL issues?

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Order of Operations

The order of operations in a SQL query is as follows:

1. FROM clause: specifies the tables to be used.
2. WHERE clause: filters rows before grouping.
3. GROUP BY clause: groups rows based on conditions.
4. HAVING clause: filters groups after grouping.
5. SELECT clause: specifies the columns to be retrieved.
6. ORDER BY clause: sorts the result set.
7. OFFSET and FETCH clauses: used to paginate the result set.

For example:

SELECT customer_id, SUM(total_amount) AS total_spent
FROM orders
WHERE order_date > '2022-01-01'
GROUP BY customer_id
HAVING SUM(total_amount) > 1000
ORDER BY total_spent DESC
OFFSET 0 ROWS
FETCH NEXT 10 ROWS ONLY;

This query:

1. Selects data from the "orders" table.
2. Filters out rows where the order date is before 2022-01-01.
3. Groups orders by customer_id.
4. Filters out groups where the total spent is less than or equal to 1000.
5. Retrieves the customer_id and total_spent columns.
6. Sorts the result set by total_spent in descending order.
7. Returns only the top 10 rows, starting from the first row (OFFSET 0).

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SQL Learning plan in 2024

|-- Week 1: Introduction to SQL
|   |-- SQL Basics
|   |   |-- What is SQL?
|   |   |-- History and Evolution of SQL
|   |   |-- Relational Databases
|   |-- Setting up for SQL
|   |   |-- Installing MySQL/PostgreSQL
|   |   |-- Setting up a Database
|   |   |-- Basic SQL Syntax
|   |-- First SQL Queries
|   |   |-- SELECT Statements
|   |   |-- WHERE Clauses
|   |   |-- Basic Filtering
|
|-- Week 2: Intermediate SQL
|   |-- Advanced SELECT Queries
|   |   |-- ORDER BY
|   |   |-- LIMIT
|   |   |-- Aliases
|   |-- Joining Tables
|   |   |-- INNER JOIN
|   |   |-- LEFT JOIN
|   |   |-- RIGHT JOIN
|   |   |-- FULL OUTER JOIN
|   |-- Aggregations
|   |   |-- COUNT, SUM, AVG, MIN, MAX
|   |   |-- GROUP BY
|   |   |-- HAVING Clauses
|
|-- Week 3: Advanced SQL Techniques
|   |-- Subqueries
|   |   |-- Basic Subqueries
|   |   |-- Correlated Subqueries
|   |-- Window Functions
|   |   |-- ROW_NUMBER, RANK, DENSE_RANK
|   |   |-- NTILE, LEAD, LAG
|   |-- Advanced Joins
|   |   |-- Self Joins
|   |   |-- Cross Joins
|   |-- Data Types and Functions
|   |   |-- Date Functions
|   |   |-- String Functions
|   |   |-- Numeric Functions
|
|-- Week 4: Database Design and Normalization
|   |-- Database Design Principles
|   |   |-- ER Diagrams
|   |   |-- Relationships and Cardinality
|   |-- Normalization
|   |   |-- First Normal Form (1NF)
|   |   |-- Second Normal Form (2NF)
|   |   |-- Third Normal Form (3NF)
|   |-- Indexes and Performance Tuning
|   |   |-- Creating Indexes
|   |   |-- Understanding Execution Plans
|   |   |-- Optimizing Queries
|
|-- Week 5: Stored Procedures and Functions
|   |-- Stored Procedures
|   |   |-- Creating Stored Procedures
|   |   |-- Parameters in Stored Procedures
|   |   |-- Error Handling
|   |-- Functions
|   |   |-- Scalar Functions
|   |   |-- Table-Valued Functions
|   |   |-- System Functions
|
|-- Week 6: Transactions and Concurrency
|   |-- Transactions
|   |   |-- ACID Properties
|   |   |-- COMMIT and ROLLBACK
|   |   |-- Savepoints
|   |-- Concurrency Control
|   |   |-- Locking Mechanisms
|   |   |-- Isolation Levels
|   |   |-- Deadlocks and How to Avoid Them
|
|-- Week 7-8: Advanced SQL Topics
|   |-- Triggers
|   |   |-- Creating and Using Triggers
|   |   |-- AFTER and BEFORE Triggers
|   |   |-- INSTEAD OF Triggers
|   |-- Views
|   |   |-- Creating Views
|   |   |-- Updating Views
|   |   |-- Indexed Views
|   |-- Security
|   |   |-- User Management
|   |   |-- Roles and Permissions
|   |   |-- SQL Injection Prevention
|
|-- Week 9-11: Real-world Applications and Projects
|   |-- Capstone Project
|   |   |-- Designing a Database Schema
|   |   |-- Implementing the Schema
|   |   |-- Writing Complex Queries
|   |   |-- Optimizing and Tuning
|   |-- ETL Processes
|   |   |-- Data Extraction
|   |   |-- Data Transformation
|   |   |-- Data Loading
|   |-- Data Analysis and Reporting
|   |   |-- Creating Reports
|   |   |-- Data Visualization with SQL
|   |   |-- Integration with BI Tools
|
|-- Week 12: Post-Project Learning
|   |-- Database Administration
|   |   |-- Backup and Restore
|   |   |-- Maintenance Plans
|   |   |-- Performance Monitoring
|   |-- SQL in the Cloud
|   |   |-- AWS RDS
|   |   |-- Google Cloud SQL
|   |   |-- Azure SQL Database
|   |-- Continuing Education
|   |   |-- Advanced SQL Topics
|   |   |-- Research Papers
|   |   |-- New Developments in SQL
|
|-- Resources and Community
|   |-- Online Courses (Coursera, Udacity)
|   |-- Books (SQL for Data Analysis, Learning SQL)
|   |-- SQL Blogs and Resources
|   |-- GitHub Repositories

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Why SQL is a Must-Have Skill?

If you're working with data, mastering SQL is non-negotiable! It’s the backbone of handling and making sense of vast datasets in any industry.

◆ Data at Your Fingertips
Effortlessly organize, retrieve, and manage large datasets to make informed decisions faster.

◆ Stay Organized
Use primary and foreign keys to keep your data accurate and connected across tables.

◆ Unlock Insights
Combine data from multiple sources and uncover trends using SQL's powerful query capabilities.

◆ Efficiency Matters
Optimize your databases with normalization and avoid unnecessary redundancy.

◆ Advanced Tools
From ACID transactions to optimizing with DELETE vs TRUNCATE, SQL makes sure your data is consistent and secure.

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Frequently asked SQL interview questions for Data Analyst/Data Engineer role-

1 - What is SQL and what are its main features?
2 - Order of writing SQL query?
3- Order of execution of SQL query?
4- What are some of the most common SQL commands?
5- What’s a primary key & foreign key?
6 - All types of joins and questions on their outputs?
7 - Explain all window functions and difference between them?
8 - What is stored procedure?
9 - Difference between stored procedure & Functions in SQL?
10 - What is trigger in SQL?
11 - Difference between where and having?

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𝟱 𝗦𝗤𝗟 𝗠𝘆𝘁𝗵𝘀 𝗗𝗲𝗯𝘂𝗻𝗸𝗲𝗱 ❌ 𝗪𝗵𝗮𝘁 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿𝘀 𝗢𝗳𝘁𝗲𝗻 𝗚𝗲𝘁 𝗪𝗿𝗼𝗻𝗴
SQL is super powerful, but some myths around it can trip up beginners. Let’s clear up five common misunderstandings and set the record straight:

𝗠𝘆𝘁𝗵 𝟭: 𝗦𝗤𝗟 𝗶𝘀 𝗷𝘂𝘀𝘁 𝗳𝗼𝗿 𝗽𝘂𝗹𝗹𝗶𝗻𝗴 𝗱𝗮𝘁𝗮.
✦ 𝗥𝗲𝗮𝗹𝗶𝘁𝘆: Nope, it’s not just for that! SQL can also create, modify, and manage databases, control access, and maintain data consistency.
✦ 𝗙𝗶𝘅 𝗶𝘁: Explore all the features of SQL, like DDL (for database design), DCL (for access control), and TCL (for transactions). It's more than just SELECT!

𝗠𝘆𝘁𝗵 𝟮: 𝗨𝘀𝗶𝗻𝗴 𝗦𝗘𝗟𝗘𝗖𝗧 * 𝗶𝘀 𝗳𝗶𝗻𝗲.
✦ 𝗥𝗲𝗮𝗹𝗶𝘁𝘆: It might be easy, but it’s not efficient. Pulling all columns wastes memory and slows down performance.
✦ 𝗙𝗶𝘅 𝗶𝘁: Only select the columns you actually need. It’s faster and cleaner.
Not great - SELECT * FROM employees;
Better - SELECT employee_id, name, department FROM employees;

𝗠𝘆𝘁𝗵 𝟯: 𝗦𝗤𝗟 𝗰𝗮𝗻'𝘁 𝗵𝗮𝗻𝗱𝗹𝗲 𝗰𝗼𝗺𝗽𝗹𝗲𝘅 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀.
✦ 𝗥𝗲𝗮𝗹𝗶𝘁𝘆: SQL can do way more than basic queries! With concepts like window functions and CTEs, you can handle really complex data analysis.
✦ 𝗙𝗶𝘅 𝗶𝘁: Learn advanced SQL features like window functions (ROW_NUMBER(), RANK()) and CTEs to up your game.
Example - Ranking employees by salary within their department
WITH ranked_salaries AS (SELECT employee_id, salary, department,
ROW_NUMBER() OVER (PARTITION BY department ORDER BY salary DESC) AS rank FROM employees)
SELECT * FROM ranked_salaries WHERE rank = 1;

𝗠𝘆𝘁𝗵 𝟰: 𝗦𝗹𝗼𝘄 𝗾𝘂𝗲𝗿𝗶𝗲𝘀 𝗮𝗿𝗲 𝗮𝗹𝘄𝗮𝘆𝘀 𝘁𝗵𝗲 𝗱𝗮𝘁𝗮𝗯𝗮𝘀𝗲’𝘀 𝗳𝗮𝘂𝗹𝘁.
✦ 𝗥𝗲𝗮𝗹𝗶𝘁𝘆: It’s usually inefficient queries causing the slowdown. Things like missing indexes or unoptimized code can be the culprit.
✦ 𝗙𝗶𝘅 𝗶𝘁: Use indexes properly, avoid complex calculations in WHERE clauses, and check your query execution plan to spot bottlenecks.

𝗠𝘆𝘁𝗵 𝟱: 𝗦𝗤𝗟 𝗶𝘀 𝗼𝘂𝘁𝗱𝗮𝘁𝗲𝗱 𝗮𝗻𝗱 𝘄𝗶𝗹𝗹 𝗯𝗲 𝗿𝗲𝗽𝗹𝗮𝗰𝗲𝗱 𝘀𝗼𝗼𝗻.
✦ 𝗥𝗲𝗮𝗹𝗶𝘁𝘆: SQL is here to stay! Despite the rise of NoSQL, SQL remains the backbone for structured data.
✦ 𝗙𝗶𝘅 𝗶𝘁: Stay current and explore how SQL integrates with big data platforms and cloud databases. It’s more relevant than ever.

Don’t let these myths hold you back. SQL is powerful, and when you understand it fully, you can do amazing things with your data.

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Top 5 SQL Functions

https://t.me/sqlanalyst

1. SELECT Statement:
- Function: Retrieving data from one or more tables.
- Example: SELECT column1, column2 FROM table WHERE condition;

2. COUNT Function:
- Function: Counts the number of rows that meet a specified condition.
- Example: SELECT COUNT(column) FROM table WHERE condition;

3. SUM Function:
- Function: Calculates the sum of values in a numeric column.
- Example: SELECT SUM(column) FROM table WHERE condition;

4. AVG Function:
- Function: Computes the average value of a numeric column.
- Example: SELECT AVG(column) FROM table WHERE condition;

5. GROUP BY Clause:
- Function: Groups rows that have the same values in specified columns into summary rows.
- Example: SELECT column, AVG(numeric_column) FROM table GROUP BY column;

These functions are fundamental in SQL and are frequently used for various data manipulation tasks, including data retrieval, aggregation, and analysis.

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35 Most Common SQL Interview Questions 👇👇

1.) Explain order of execution of SQL.
2.) What is difference between where and having?
3.) What is the use of group by?
4.) Explain all types of joins in SQL?
5.) What are triggers in SQL?
6.) What is stored procedure in SQL
7.) Explain all types of window functions?
(Mainly rank, row_num, dense_rank, lead & lag)
8.) What is difference between Delete and Truncate?
9.) What is difference between DML, DDL and DCL?
10.) What are aggregate function and when do we use them? explain with few example.
11.) Which is faster between CTE and Subquery?
12.) What are constraints and types of Constraints?
13.) Types of Keys?
14.) Different types of Operators ?
15.) Difference between Group By and Where?
16.) What are Views?
17.) What are different types of constraints?
18.) What is difference between varchar and nvarchar?
19.) Similar for char and nchar?
20.) What are index and their types?
21.) What is an index? Explain its different types.
22.) List the different types of relationships in SQL.
23.) Differentiate between UNION and UNION ALL.
24.) How many types of clauses in SQL?
25.) What is the difference between UNION and UNION ALL in SQL?
26.) What are the various types of relationships in SQL?
27.) Difference between Primary Key and Secondary Key?
28.) What is the difference between where and having?
29.) Find the second highest salary of an employee?
30.) Write retention query in SQL?
31.) Write year-on-year growth in SQL?
32.) Write a query for cummulative sum in SQL?
33.) Difference between Function and Store procedure ?
34.) Do we use variable in views?
35.) What are the limitations of views?

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SQL, or Structured Query Language, is a domain-specific language used to manage and manipulate relational databases. Here's a brief A-Z overview by @sqlanalyst

A - Aggregate Functions: Functions like COUNT, SUM, AVG, MIN, and MAX used to perform operations on data in a database.

B - BETWEEN: A SQL operator used to filter results within a specific range.

C - CREATE TABLE: SQL statement for creating a new table in a database.

D - DELETE: SQL statement used to delete records from a table.

E - EXISTS: SQL operator used in a subquery to test if a specified condition exists.

F - FOREIGN KEY: A field in a database table that is a primary key in another table, establishing a link between the two tables.

G - GROUP BY: SQL clause used to group rows that have the same values in specified columns.

H - HAVING: SQL clause used in combination with GROUP BY to filter the results.

I - INNER JOIN: SQL clause used to combine rows from two or more tables based on a related column between them.

J - JOIN: Combines rows from two or more tables based on a related column.

K - KEY: A field or set of fields in a database table that uniquely identifies each record.

L - LIKE: SQL operator used in a WHERE clause to search for a specified pattern in a column.

M - MODIFY: SQL command used to modify an existing database table.

N - NULL: Represents missing or undefined data in a database.

O - ORDER BY: SQL clause used to sort the result set in ascending or descending order.

P - PRIMARY KEY: A field in a table that uniquely identifies each record in that table.

Q - QUERY: A request for data from a database using SQL.

R - ROLLBACK: SQL command used to undo transactions that have not been saved to the database.

S - SELECT: SQL statement used to query the database and retrieve data.

T - TRUNCATE: SQL command used to delete all records from a table without logging individual row deletions.

U - UPDATE: SQL statement used to modify the existing records in a table.

V - VIEW: A virtual table based on the result of a SELECT query.

W - WHERE: SQL clause used to filter the results of a query based on a specified condition.

X - (E)XISTS: Used in conjunction with SELECT to test the existence of rows returned by a subquery.

Z - ZERO: Represents the absence of a value in numeric fields or the initial state of boolean fields.

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SQL Interview Questions which can be asked in a Data Analyst Interview.

1️⃣ What is difference between Primary key and Unique key?

◼Primary key- A column or set of columns which uniquely identifies each record in a table. It can't contain null values and only one primary key
can exist in a table.

◼Unique key-Similar to primary key it also uniquely identifies each record in a table and can contain null values.Multiple Unique key can exist in a table.

2️⃣ What is a Candidate key?

◼A key or set of keys that uniquely identifies each record in a table.It is a combination of Primary and Alternate key.

3️⃣ What is a Constraint?

◼Specific rule or limit that we define in our table. E.g - NOT NULL,AUTO INCREMENT

4️⃣ Can you differentiate between TRUNCATE and DELETE?

◼TRUNCATE is a DDL command. It deletes the entire data from a table but preserves the structure of table.It doesn't deletes the data row by row hence faster than DELETE command, while DELETE is a DML command and it deletes the entire data based on specified condition else deletes the entire data,also it deletes the data row by row hence slower than TRUNCATE command.

5️⃣ What is difference between 'View' and 'Stored Procedure'?

◼A View is a virtual table that gets data from the base table .It is basically a Select statement,while Stored Procedure is a sql statement or set of sql statement stored on database server.

6️⃣ What is difference between a Common Table Expression and temporary table?

◼CTE is a temporary result set that is defined within execution scope of a single SELECT ,DELETE,UPDATE statement while temporary table is stored in TempDB and gets deleted once the session expires.

7️⃣ Differentiate between a clustered index and a non-clustered index?

◼ A clustered index determines physical ordering of data in a table and a table can have only one clustered index while a non-clustered index is analogous to index of a book where index is stored at one place and data at other place and index will have pointers to storage location of the data,a table can have more than one non-clustered index.

8️⃣ Explain triggers ?

◼They are sql codes which are automatically executed in response to certain events on a table.They are used to maintain integrity of data.

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✍️Best practices for writing SQL 📊queries:

1- Write SQL keywords in capital letters.

2- Use table aliases with columns when you are joining multiple tables.

3- Never use select *, always mention list of columns in select clause.

4- Add useful comments wherever you write complex logic. Avoid too many comments.

5- Use joins instead of subqueries when possible for better performance.

6- Create CTEs instead of multiple sub queries , it will make your query easy to read.

7- Join tables using JOIN keywords instead of writing join condition in where clause for better readability.

8- Never use order by in sub queries , It will unnecessary increase runtime.

9- If you know there are no duplicates in 2 tables, use UNION ALL instead of UNION for better performance.

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SQL From Basic to Advanced level

Basic SQL is ONLY 7 commands:
- SELECT
- FROM
- WHERE (also use SQL comparison operators such as =, =, etc.)
- ORDER BY
- Aggregate functions such as SUM, AVERAGE, COUNT etc.
- GROUP BY
- CREATE, INSERT, DELETE, etc.
You can do all this in just one morning.

Once you know these, take the next step and learn commands like:
- LEFT JOIN
- INNER JOIN
- LIKE
- IN
- CASE WHEN
- HAVING (undertstand how it's different from GROUP BY)
- UNION ALL
This should take another day.

Once both basic and intermediate are done, start learning more advanced SQL concepts such as:
- Subqueries (when to use subqueries vs CTE?)
- CTEs (WITH AS)
- Stored Procedures
- Triggers
- Window functions (LEAD, LAG, PARTITION BY, RANK, DENSE RANK)
These can be done in a couple of days.
Learning these concepts is NOT hard at all

- what takes time is practice and knowing what command to use when. How do you master that?
- First, create a basic SQL project
- Then, work on an intermediate SQL project (search online) -

Lastly, create something advanced on SQL with many CTEs, subqueries, stored procedures and triggers etc.

This is ALL you need to become a badass in SQL, and trust me when I say this, it is not rocket science. It's just logic.

Remember that practice is the key here. It will be more clear and perfect with the continous practice

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Data Analyst Roadmap:

- Tier 1: Excel & SQL
- Tier 2: Data Cleaning & Exploratory Data Analysis (EDA)
- Tier 3: Data Visualization & Business Intelligence (BI) Tools
- Tier 4: Statistical Analysis & Machine Learning Basics

Then build projects that include:

- Data Collection
- Data Cleaning
- Data Analysis
- Data Visualization

And if you want to make your portfolio stand out more:

- Solve real business problems
- Provide clear, impactful insights
- Create a presentation
- Record a video presentation
- Target specific industries
- Reach out to companies

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The SQL EXISTS operator tests the existence of any value in a subquery i.e. it executes the outer SQL query only if the subquery is not NULL (empty result-set),making it perfect for validating the presence of related data.

The result of EXISTS is a boolean value either True or False

We can also use the NOT operator to inverse the working of the EXISTS clause. The SQL command executes if the subquery returns an empty result-set.



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