SQL for Data Analysis
Find top SQL resources from global universities, cool projects, and learning materials for data analytics. For promotions: @coderfun Buy ads: https://telega.io/c/sqlanalyst Useful links: heylink.me/DataAnalytics
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01 𝑪𝒐𝒎𝒑𝒓𝒆𝒉𝒆𝒏𝒔𝒊𝒗𝒆 𝒓𝒐𝒂𝒅𝒎𝒂𝒑 𝒕𝒐 𝒃𝒆𝒄𝒐𝒎𝒊𝒏𝒈 𝒂 𝒎𝒂𝒔𝒕𝒆𝒓 𝒊𝒏 𝑺𝑸𝑳:
1. 𝑼𝒏𝒅𝒆𝒓𝒔𝒕𝒂𝒏𝒅 𝒕𝒉𝒆 𝑩𝒂𝒔𝒊𝒄𝒔 𝒐𝒇 𝑺𝑸𝑳
𝐀. 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞𝐬
𝐖𝐡𝐚𝐭 𝐢𝐬 𝐚 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞?: Understanding the concept of databases and relational databases.
𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 (𝐃𝐁𝐌𝐒): Learn about different DBMS like MySQL, PostgreSQL, SQL Server, Oracle.
𝐁. 𝐁𝐚𝐬𝐢𝐜 𝐒𝐐𝐋 𝐂𝐨𝐦𝐦𝐚𝐧𝐝𝐬
𝐃𝐚𝐭𝐚 𝐑𝐞𝐭𝐫𝐢𝐞𝐯𝐚𝐥:
𝐒𝐄𝐋𝐄𝐂𝐓: Basic retrieval of data.
𝐖𝐇𝐄𝐑𝐄: Filtering data based on conditions.
𝐎𝐑𝐃𝐄𝐑 𝐁𝐘: Sorting results.
𝐋𝐈𝐌𝐈𝐓: Limiting the number of rows returned.
𝐃𝐚𝐭𝐚 𝐌𝐚𝐧𝐢𝐩𝐮𝐥𝐚𝐭𝐢𝐨𝐧:
𝐈𝐍𝐒𝐄𝐑𝐓: Adding new data.
𝐔𝐏𝐃𝐀𝐓𝐄: Modifying existing data.
𝐃𝐄𝐋𝐄𝐓𝐄: Removing data.
2. 𝐈𝐧𝐭𝐞𝐫𝐦𝐞𝐝𝐢𝐚𝐭𝐞 𝐒𝐐𝐋 𝐒𝐤𝐢𝐥𝐥𝐬
𝐀. 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐃𝐚𝐭𝐚 𝐑𝐞𝐭𝐫𝐢𝐞𝐯𝐚𝐥
𝐉𝐎𝐈𝐍𝐬: Understanding different types of joins (INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN).
𝐀𝐠𝐠𝐫𝐞𝐠𝐚𝐭𝐞 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐬: Using functions like COUNT, SUM, AVG, MIN, MAX.
𝐆𝐑𝐎𝐔𝐏 𝐁𝐘: Grouping data to perform aggregate calculations.
𝐇𝐀𝐕𝐈𝐍𝐆: Filtering groups based on aggregate values.
𝐁. 𝐒𝐮𝐛𝐪𝐮𝐞𝐫𝐢𝐞𝐬 𝐚𝐧𝐝 𝐍𝐞𝐬𝐭𝐞𝐝 𝐐𝐮𝐞𝐫𝐢𝐞𝐬
𝐒𝐮𝐛𝐪𝐮𝐞𝐫𝐢𝐞𝐬: Using queries within queries.
𝐂𝐨𝐫𝐫𝐞𝐥𝐚𝐭𝐞𝐝 𝐒𝐮𝐛𝐪𝐮𝐞𝐫𝐢𝐞𝐬: Subqueries that reference columns from the outer query.
𝑪. 𝑫𝒂𝒕𝒂 𝑫𝒆𝒇𝒊𝒏𝒊𝒕𝒊𝒐𝒏 𝑳𝒂𝒏𝒈𝒖𝒂𝒈𝒆 (𝑫𝑫𝑳)
𝐂𝐫𝐞𝐚𝐭𝐢𝐧𝐠 𝐓𝐚𝐛𝐥𝐞𝐬: CREATE TABLE.
𝐌𝐨𝐝𝐢𝐟𝐲𝐢𝐧𝐠 𝐓𝐚𝐛𝐥𝐞𝐬: ALTER TABLE.
𝑹𝒆𝒎𝒐𝒗𝒊𝒏𝒈 𝑻𝒂𝒃𝒍𝒆𝒔: DROP TABLE.
3. 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐒𝐐𝐋 𝐓𝐞𝐜𝐡𝐧𝐢𝐪𝐮𝐞𝐬
𝐀. 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧
𝐈𝐧𝐝𝐞𝐱𝐞𝐬: Understanding and creating indexes to speed up queries.
𝐐𝐮𝐞𝐫𝐲 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Techniques to write efficient SQL queries.
𝐁. 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐒𝐐𝐋 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐬
𝐖𝐢𝐧𝐝𝐨𝐰 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐬: Using functions like ROW_NUMBER, RANK, DENSE_RANK, LEAD, LAG.
𝐂𝐓𝐄 (𝐂𝐨𝐦𝐦𝐨𝐧 𝐓𝐚𝐛𝐥𝐞 𝐄𝐱𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧𝐬): Using WITH to create temporary result sets.
𝐂. 𝐓𝐫𝐚𝐧𝐬𝐚𝐜𝐭𝐢𝐨𝐧𝐬 𝐚𝐧𝐝 𝐂𝐨𝐧𝐜𝐮𝐫𝐫𝐞𝐧𝐜𝐲
𝐓𝐫𝐚𝐧𝐬𝐚𝐜𝐭𝐢𝐨𝐧𝐬: Using BEGIN, COMMIT, ROLLBACK.
𝐂𝐨𝐧𝐜𝐮𝐫𝐫𝐞𝐧𝐜𝐲 𝐂𝐨𝐧𝐭𝐫𝐨𝐥: Understanding isolation levels and locking mechanisms.
4. 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐚𝐥 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐚𝐧𝐝 𝐑𝐞𝐚𝐥-𝐖𝐨𝐫𝐥𝐝 𝐒𝐜𝐞𝐧𝐚𝐫𝐢𝐨𝐬
𝐀. 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐃𝐞𝐬𝐢𝐠𝐧
𝐍𝐨𝐫𝐦𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Understanding normal forms and how to normalize databases.
𝐄𝐑 𝐃𝐢𝐚𝐠𝐫𝐚𝐦𝐬: Creating Entity-Relationship diagrams to model databases.
𝐁. 𝐃𝐚𝐭𝐚 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧
𝐄𝐓𝐋 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐞𝐬: Extract, Transform, Load processes for data integration.
𝐒𝐭𝐨𝐫𝐞𝐝 𝐏𝐫𝐨𝐜𝐞𝐝𝐮𝐫𝐞𝐬 𝐚𝐧𝐝 𝐓𝐫𝐢𝐠𝐠𝐞𝐫𝐬: Writing and using stored procedures and triggers for complex logic and automation.
𝐂. 𝐂𝐚𝐬𝐞 𝐒𝐭𝐮𝐝𝐢𝐞𝐬 𝐚𝐧𝐝 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬
𝐑𝐞𝐚𝐥-𝐖𝐨𝐫𝐥𝐝 𝐒𝐜𝐞𝐧𝐚𝐫𝐢𝐨𝐬: Work on case studies involving complex database operations.
𝐂𝐚𝐩𝐬𝐭𝐨𝐧𝐞 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬: Develop comprehensive projects that showcase your SQL expertise.
𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞𝐬 𝐚𝐧𝐝 𝐓𝐨𝐨𝐥𝐬
𝐁𝐨𝐨𝐤𝐬: "SQL in 10 Minutes, Sams Teach Yourself" by Ben Forta, "SQL for Data Scientists" by Renee M. P. Teate.
𝐎𝐧𝐥𝐢𝐧𝐞 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬: Coursera, Udacity, edX, Khan Academy.
𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬: LeetCode, HackerRank, Mode Analytics, SQLZoo.
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Here you can find quick SQL Revision Notes👇
https://topmate.io/analyst/864817
Hope it helps :) | 1 084 | 26 | Loading... |
02 🔔🔔Happy to Announce that we would be conducting Live Instructor led "SQL - Basics to Intermediate" Workshop on 8th June 2024. Duration 4 hrs.
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🔔What would be syllabus which would be covered?🔔
SQL Overview
Database overview
Basic Datatypes
Retrieval of Data
(Select, From, Where ,
Distinct, order By)
Working with Operators
BODMAS Rule (working
with multiple operators)
Basic SQL functions
Wildcard
Concept of Null
Practice examples
Group By
Having vs Where
Aggregate Functions
DDL vs DML
Create, Insert, Update,
Delete, Drop, Alter,
Truncate
Joins – Understanding
and working with Joins
Subqueries
Practice examples and
QUIZ
Introduction to Advanced
SQL
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03 𝗦𝗤𝗟 𝗖𝗵𝗲𝗮𝘁 𝗦𝗵𝗲𝗲𝘁 | 3 781 | 19 | Loading... |
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05 SQL Zero to Hero
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07 Top 10 SQL concepts for data analysts
1. Database: A database is a structured collection of data that is organized and managed for easy access and retrieval. It stores data in tables, which are made up of rows and columns.
2. SQL (Structured Query Language): SQL is a programming language used to communicate with and manipulate databases. It allows data analysts to retrieve, insert, update, and delete data from a database.
3. Tables: Tables are the basic building blocks of a database. They consist of rows (records) and columns (fields) that store data in a structured format.
4. Queries: Queries are SQL statements used to retrieve specific data from a database. They can be simple or complex, involving multiple tables and conditions.
5. Joins: Joins are used to combine data from multiple tables based on a common field. They allow data analysts to retrieve related information from different tables in a single query.
6. Aggregation Functions: Aggregation functions, such as SUM, COUNT, AVG, MIN, and MAX, are used to perform calculations on groups of data. They are commonly used to summarize and analyze large datasets.
7. Filtering: Filtering allows data analysts to retrieve specific data based on certain conditions. It involves using the WHERE clause in SQL queries to specify the criteria for selecting records.
8. Sorting: Sorting allows data analysts to arrange data in a specific order. It involves using the ORDER BY clause in SQL queries to sort records based on one or more columns.
9. Subqueries: Subqueries are queries nested within another query. They allow data analysts to perform complex operations by using the results of one query as input for another query.
10. Data Manipulation Language (DML): DML statements, such as INSERT, UPDATE, and DELETE, are used to modify data in a database. Data analysts use these statements to insert new records, update existing records, or delete unwanted records.
Here you can find quick SQL Revision Notes👇
https://topmate.io/analyst/864817
Hope it helps :) | 5 876 | 36 | Loading... |
08 📊🚀A beginner's roadmap for learning SQL:
🔹Understand Basics:
Learn what SQL is and its purpose in managing relational databases.
Understand basic database concepts like tables, rows, columns, and relationships.
🔹Learn SQL Syntax:
Familiarize yourself with SQL syntax for common commands like SELECT, INSERT, UPDATE, DELETE.
Understand clauses like WHERE, ORDER BY, GROUP BY, and JOIN.
🔹Setup a Database:
Install a relational database management system (RDBMS) like MySQL, SQLite, or PostgreSQL.
Practice creating databases, tables, and inserting data.
🔹Retrieve Data (SELECT):
Learn to retrieve data from a database using SELECT statements.
Practice filtering data using WHERE clause and sorting using ORDER BY.
🔹Modify Data (INSERT, UPDATE, DELETE):
Understand how to insert new records, update existing ones, and delete data.
Be cautious with DELETE to avoid unintentional data loss.
🔹Working with Functions:
Explore SQL functions like COUNT, AVG, SUM, MAX, MIN for data analysis.
Understand string functions, date functions, and mathematical functions.
🔹Data Filtering and Sorting:
Learn advanced filtering techniques using AND, OR, and IN operators.
Practice sorting data using multiple columns.
🔹Table Relationships (JOIN):
Understand the concept of joining tables to retrieve data from multiple tables.
Learn about INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.
🔹Grouping and Aggregation:
Explore GROUP BY clause to group data based on specific columns.
Understand aggregate functions for summarizing data (SUM, AVG, COUNT).
🔹Subqueries:
Learn to use subqueries to perform complex queries.
Understand how to use subqueries in SELECT, WHERE, and FROM clauses.
🔹Indexes and Optimization:
Gain knowledge about indexes and their role in optimizing queries.
Understand how to optimize SQL queries for better performance.
🔹Transactions and ACID Properties:
Learn about transactions and the ACID properties (Atomicity, Consistency, Isolation, Durability).
Understand how to use transactions to maintain data integrity.
🔹Normalization:
Understand the basics of database normalization to design efficient databases.
Learn about 1NF, 2NF, 3NF, and BCNF.
🔹Backup and Recovery:
Understand the importance of database backups.
Learn how to perform backups and recovery operations.
🔹Practice and Projects:
Apply your knowledge through hands-on projects.
Practice on platforms like LeetCode, HackerRank, or build your own small database-driven projects.
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10 Complete topics & subtopics of hashtag#SQL for Data Engineer role:-
𝟭. 𝗕𝗮𝘀𝗶𝗰 𝗦𝗤𝗟 𝗦𝘆𝗻𝘁𝗮𝘅:
SQL keywords
Data types
Operators
SQL statements (SELECT, INSERT, UPDATE, DELETE)
𝟮. 𝗗𝗮𝘁𝗮 𝗗𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 (𝗗𝗗𝗟):
CREATE TABLE
ALTER TABLE
DROP TABLE
Truncate table
𝟯. 𝗗𝗮𝘁𝗮 𝗠𝗮𝗻𝗶𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 (𝗗𝗠𝗟):
SELECT statement (SELECT, FROM, WHERE, ORDER BY, GROUP BY, HAVING, JOINs)
INSERT statement
UPDATE statement
DELETE statement
𝟰. 𝗔𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗲 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀:
SUM, AVG, COUNT, MIN, MAX
GROUP BY clause
HAVING clause
𝟱. 𝗗𝗮𝘁𝗮 𝗖𝗼𝗻𝘀𝘁𝗿𝗮𝗶𝗻𝘁𝘀:
Primary Key
Foreign Key
Unique
NOT NULL
CHECK
𝟲. 𝗝𝗼𝗶𝗻𝘀:
INNER JOIN
LEFT JOIN
RIGHT JOIN
FULL OUTER JOIN
Self Join
Cross Join
𝟳. 𝗦𝘂𝗯𝗾𝘂𝗲𝗿𝗶𝗲𝘀:
Types of subqueries (scalar, column, row, table)
Nested subqueries
Correlated subqueries
𝟴. 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗦𝗤𝗟 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀:
String functions (CONCAT, LENGTH, SUBSTRING, REPLACE, UPPER, LOWER)
Date and time functions (DATE, TIME, TIMESTAMP, DATEPART, DATEADD)
Numeric functions (ROUND, CEILING, FLOOR, ABS, MOD)
Conditional functions (CASE, COALESCE, NULLIF)
𝟵. 𝗩𝗶𝗲𝘄𝘀:
Creating views
Modifying views
Dropping views
𝟭𝟬. 𝗜𝗻𝗱𝗲𝘅𝗲𝘀:
Creating indexes
Using indexes for query optimization
𝟭𝟭. 𝗧𝗿𝗮𝗻𝘀𝗮𝗰𝘁𝗶𝗼𝗻𝘀:
ACID properties
Transaction management (BEGIN, COMMIT, ROLLBACK, SAVEPOINT)
Transaction isolation levels
𝟭𝟮. 𝗗𝗮𝘁𝗮 𝗜𝗻𝘁𝗲𝗴𝗿𝗶𝘁𝘆 𝗮𝗻𝗱 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆:
Data integrity constraints (referential integrity, entity integrity)
GRANT and REVOKE statements (granting and revoking permissions)
Database security best practices
𝟭𝟯. 𝗦𝘁𝗼𝗿𝗲𝗱 𝗣𝗿𝗼𝗰𝗲𝗱𝘂𝗿𝗲𝘀 𝗮𝗻𝗱 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀:
Creating stored procedures
Executing stored procedures
Creating functions
Using functions in queries
𝟭𝟰. 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻:
Query optimization techniques (using indexes, optimizing joins, reducing subqueries)
Performance tuning best practices
𝟭𝟱. 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗦𝗤𝗟 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀:
Recursive queries
Pivot and unpivot operations
Window functions (Row_number, rank, dense_rank, lead & lag)
CTEs (Common Table Expressions)
Dynamic SQL
Here you can find quick SQL Revision Notes👇
https://topmate.io/analyst/864817
Hope it helps :) | 2 121 | 7 | Loading... |
11 20 medium-level SQL interview questions:
1. Write a SQL query to find the second-highest salary.
2. How would you optimize a slow SQL query?
3. What is the difference between INNER JOIN and OUTER JOIN?
4. Write a SQL query to find the top 3 departments with the highest average salary.
5. How do you handle duplicate rows in a SQL query?
6. Write a SQL query to find the employees who have the same name and work in the same department.
7. What is the difference between UNION and UNION ALL?
8. Write a SQL query to find the departments with no employees.
9. How do you use indexing to improve SQL query performance?
10. Write a SQL query to find the employees who have worked for more than 5 years.
11. What is the difference between SUBQUERY and JOIN?
12. Write a SQL query to find the top 2 products with the highest sales.
13. How do you use stored procedures to improve SQL query performance?
14. Write a SQL query to find the customers who have placed an order but have not made a payment.
15. What is the difference between GROUP BY and HAVING?
16. Write a SQL query to find the employees who work in the same department as their manager.
17. How do you use window functions to solve complex queries?
18. Write a SQL query to find the top 3 products with the highest average price.
19. What is the difference between TRUNCATE and DELETE?
20. Write a SQL query to find the employees who have not taken any leave in the last 6 months.
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12 10 Basic SQL interview questions
1. What is SQL and what are its uses?
2. Explain the difference between SQL and NoSQL databases.
3. Write a query to fetch all records from a table named Employees.
4. How do you create a table in SQL? Provide an example.
5. What is a primary key? How do you define it in a table?
6. What is a foreign key? How do you create one?
7. What is the difference between CHAR and VARCHAR data types?
8. Write a query to retrieve unique values from a column in a table.
9. How can you count the number of records in a table?
10. What is the use of the WHERE clause in SQL? Provide an example.
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13 How Query is Executed
Order of SQL query execution is not the same as order query is written.
You probably noticed that when you write SELECT count(*) AS column_name, you can't use that column_name in WHERE or GROUP BY clause. It's because select clause in which you defined your alias is not executed yet!
Each query begins with finding the data that we need in a database, and then filtering that data down into something that can be processed and understood as quickly as possible. Because each part of the query is executed sequentially, it's important to understand the order of execution so that you know what results are accessible where.
In general, SQL queries are executed in the following order:
1. FROM: The first step is to identify the tables or views involved in the query. This is specified in the FROM clause of the query.
2. JOIN: If the query involves multiple tables and requires a join operation, the join conditions are evaluated to combine the data from different tables.
3. WHERE: The WHERE clause is applied to filter the rows based on specified conditions. Rows that do not meet the conditions are eliminated from further processing.
4. GROUP BY: If the query includes a GROUP BY clause, the rows are grouped based on the specified columns.
5. HAVING: If a HAVING clause is present, it is applied to filter the groups generated by the GROUP BY clause. Groups that do not meet the conditions are eliminated.
6. SELECT: The SELECT clause is applied to determine the columns to be included in the result set. Any calculations or functions specified in the SELECT clause are also evaluated at this stage.
7. DISTINCT: If the query includes the DISTINCT keyword, duplicate rows are removed from the result set.
8. ORDER BY: If an ORDER BY clause is present, the result set is sorted based on the specified columns.
9. LIMIT/OFFSET: If the query includes a LIMIT and/or OFFSET clause, the result set is limited to a specific number of rows and/or skipped by a certain number of rows.
It’s important to note that not all queries will include every step mentioned above. The order of execution may vary depending on the specific query and the presence of different clauses. | 7 797 | 49 | Loading... |
14 Here are five of the most commonly used SQL queries in data science:
1. SELECT and FROM Clauses
- Basic data retrieval: SELECT column1, column2 FROM table_name;
2. WHERE Clause
- Filtering data: SELECT * FROM table_name WHERE condition;
3. GROUP BY and Aggregate Functions
- Summarizing data: SELECT column1, COUNT(*), AVG(column2) FROM table_name GROUP BY column1;
4. JOIN Operations
- Combining data from multiple tables:
SELECT a.column1, b.column2
FROM table1 a
JOIN table2 b ON a.common_column = b.common_column;
5. Subqueries and Nested Queries
- Advanced data retrieval:
SELECT column1
FROM table_name
WHERE column2 IN (SELECT column2 FROM another_table WHERE condition);
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15 Essential SQL Interview Questions based on Basic, Intermediate & Advance level
✅ Basic Level
1. Explain the difference between drop and truncate.
2. What are Constraints in SQL?
3. Describe the use of the SELECT statement in SQL.
4. What is a primary key in SQL?
5. Explain the difference between CHAR and VARCHAR data types in SQL.
6. What is a foreign key in SQL?
7. How do you use the GROUP BY statement in SQL?
8. What is a JOIN in SQL, and can you describe a scenario where you would use it?
9. How does the WHERE clause work in SQL?
10. Explain the use of the INSERT statement in SQL.
✅Intermediate Level
1. Describe the Difference Between Window Functions and Aggregate Functions in SQL.
2. Write a SQL query to find the top three products with the highest revenue in the last quarter from a sales database.
3. What do you understand by sub-queries in SQL?
4. What is CTE in SQL?
5. Explain the use of the HAVING clause in SQL.
6. How do you implement pagination in SQL queries?
7. Describe the differences between INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.
8. Explain the concept of indexing in SQL and its benefits.
9. How can you prevent SQL injection in your queries?
10. Write a SQL query to find the second highest salary in a given table.
✅ Advanced Level
1. Describe a SQL query challenge you faced related to optimizing database performance.
2. What is a Recursive Stored Procedure in SQL?
3. What are the subsets of SQL?
4. How do you use window functions for running totals and moving averages?
5. Explain the process and considerations for denormalizing a database.
6. Discuss the implications and solutions for dealing with NULL values in SQL operations.
7. How do you handle large datasets and optimize queries for big data in SQL?
8. Describe how to implement transaction control in SQL and its importance.
9. Explain the concept of materialized views in SQL and their use cases.
10. Discuss strategies for database sharding and partitioning in SQL and their impact on performance.
Here you can find essential SQL Interview Resources👇
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16 Preparing for an SQL interview? Here are some crucial SQL query questions you should be ready to tackle:
1. How do you retrieve all columns from a table?
2. What SQL statement is used to filter records?
3. How can you join two tables? Explain different types of JOINs.
4. What is the difference between WHERE and HAVING clauses?
5. How do you count the number of records in a table?
6. How do you calculate average, sum, minimum, and maximum values in a column?
7. What is a subquery, and how do you use it?
8. Explain the difference between correlated and non-correlated subqueries.
9. How do you optimize a slow-running query?
10. What are indexes, and how do they improve query performance?
11. How do you insert, update, and delete records in a table?
12. What is the difference between TRUNCATE and DELETE statements?
13. How do you create, alter, and drop a table?
14. What are constraints, and how do you implement them?
15. What is a transaction, and why is it important in SQL?
16. Explain COMMIT, ROLLBACK, and SAVEPOINT.
17. What is normalization, and why is it important?
18. Explain the different normal forms (1NF, 2NF, 3NF, BCNF).
19. What are window functions, and how do you use them?
20. Explain ROW_NUMBER(), RANK(), and DENSE_RANK().
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17 Roadmap to learn SQL in 14 days:
1. Basics (Days 1-3):
- Learn basic SQL syntax: SELECT, FROM, WHERE, etc.
- Understand how to retrieve data from a single table.
- Practice creating simple queries and filtering data.
2. Advanced Queries (Days 4-6):
- Dive deeper into SQL functions like GROUP BY, ORDER BY, and JOIN.
- Learn about aggregate functions (SUM, AVG, COUNT, etc.) and their usage.
- Practice writing more complex queries involving multiple tables.
3. Data Manipulation (Days 7-9):
- Understand how to insert, update, and delete data in SQL tables.
- Learn about transaction control and handling errors.
- Practice performing various data manipulation operations on a sample database.
4. Database Design (Days 10-11):
- Learn about database normalization and denormalization.
- Understand primary keys, foreign keys, and their importance in database design.
- Practice designing a simple database schema.
5. Advanced Topics and Practice (Days 12-14):
- Explore more advanced SQL topics such as subqueries, views, and stored procedures.
- Practice solving real-world problems using SQL.
- Review and reinforce your learning through online exercises and quizzes.
Here you can find essential SQL Interview Resources👇
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18 I have compiled the list of some good sql interview questions. Here is the breakdown:
1. What is the purpose of the GROUP BY clause in SQL? Provide an example.
2. Explain the difference between an INNER JOIN and a LEFT JOIN with examples.
3. Discuss the role of the WHERE clause in SQL queries and provide examples of its usage.
4. Explain the concept of database transactions and the ACID properties.
5. Describe the benefits of using subqueries in SQL and provide a scenario where they would be useful.
6. Discuss the differences between the CHAR and VARCHAR data types in SQL.
7. Explain the purpose of the ORDER BY clause in SQL queries and provide examples.
8. Describe the importance of data integrity constraints such as NOT NULL, UNIQUE, and CHECK constraints in SQL databases.
9. Discuss the advantages and disadvantages of using stored procedures
Explain the difference between an aggregate function and a scalar function in SQL, with examples.
10. Discuss the role of the COMMIT and ROLLBACK statements in SQL transactions.
11. Explain the purpose of the LIKE operator in SQL and provide examples of its usage.
12. Describe the concept of normalization forms (1NF, 2NF, 3NF) and why they are important in database design.
13. Discuss the differences between a clustered and non-clustered index in SQL.
14. Explain the concept of data warehousing and how it differs from traditional relational databases.
15. Describe the benefits of using database triggers and provide examples of their usage.
16. Discuss the concept of database concurrency control and how it is achieved in SQL databases.
17. Explain the role of the SELECT INTO statement in SQL and provide examples of its usage.
18. Describe the differences between a database view and a materialized view in SQL.
19. Discuss the advantages of using parameterized queries in SQL applications.
20. Write a query to retrieve all employees who have a salary greater than $100,000.
21. Create a query to display the total number of orders placed in the last month.
22. Write a query to find the average order value for each customer.
23. Create a query to count the number of distinct products sold in the past week.
24. Write a query to find the top 10 customers with the highest total order amount.
Here you can find essential SQL Interview Resources👇
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19 ChatGPT Prompting Cheatsheet
👇👇
https://t.me/AI_Best_Tools/210 | 6 813 | 10 | Loading... |
20 𝐓𝐨𝐩 𝐜𝐨𝐦𝐩𝐚𝐧𝐲 𝐢𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐒𝐐𝐋 𝐑𝐞𝐚𝐥 𝐖𝐨𝐫𝐥𝐝 𝐒𝐜𝐞𝐧𝐞𝐫𝐢𝐨:
𝐒𝐜𝐞𝐧𝐞𝐫𝐢𝐨:
You're working as a data analyst for a healthcare provider organization. The organization manages patient data in a SQL Server database, including information about medical appointments, diagnoses, treatments, and patient demographics. Your task is to analyze the data to improve patient care, operational efficiency, and resource allocation.
𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝟒:
How would you identify patients who are at risk of missing their upcoming appointments based on their historical appointment attendance patterns?
𝐀𝐧𝐚𝐥𝐲𝐳𝐞 𝟒:
To identify patients at risk of missing their upcoming appointments based on their historical attendance patterns, I would query the appointments table to retrieve data on past appointments for each patient. Then, I would calculate metrics such as the percentage of attended appointments and the average time between appointments for each patient. Patients with a low attendance rate or irregular appointment intervals could be flagged as at-risk for missing future appointments.
𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝟓:
How would you analyze the effectiveness of different treatments for a specific medical condition based on patient outcomes?
𝐀𝐧𝐚𝐥𝐲𝐳𝐞 𝟓:
To analyze the effectiveness of different treatments for a specific medical condition based on patient outcomes, I would query the treatments table to retrieve data on treatments administered to patients with the target medical condition. Then, I would join this data with patient outcome data, such as recovery status or symptom improvement, and possibly include factors like treatment duration or dosage. Statistical analysis techniques, such as comparing mean outcomes across treatment groups or conducting regression analysis, could be used to assess treatment effectiveness.
𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝟔:
How would you analyze patient demographics to identify disparities in healthcare access or outcomes?
𝐀𝐧𝐚𝐥𝐲𝐳𝐞 𝟔:
To analyze patient demographics and identify disparities in healthcare access or outcomes, I would query the patients table to retrieve demographic information such as age, gender, ethnicity, and socioeconomic status. Then, I would analyze this data in conjunction with healthcare utilization metrics, such as frequency of medical visits, prevalence of chronic conditions, or adherence to treatment plans. Statistical tests, such as chi-square tests or regression analysis, could be used to identify significant differences in healthcare access or outcomes across demographic groups.
Here you can find essential SQL Interview Resources👇
https://topmate.io/analyst/864764
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21 https://t.me/analystcommunity | 7 875 | 3 | Loading... |
22 https://www.linkedin.com/posts/sql-analysts_sql-quick-notes-activity-7196358639568220160-Azh2?utm_source=share&utm_medium=member_android | 9 471 | 22 | Loading... |
23 𝐓𝐨𝐩 𝐜𝐨𝐦𝐩𝐚𝐧𝐲 𝐢𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐒𝐐𝐋 𝐑𝐞𝐚𝐥 𝐖𝐨𝐫𝐥𝐝 𝐒𝐜𝐞𝐧𝐞𝐫𝐢𝐨:
𝐒𝐜𝐞𝐧𝐞𝐫𝐢𝐨:
You're a data analyst working for a retail company that wants to optimize its sales strategies. The company has a SQL Server database that contains various tables related to sales transactions, customer information, product details, and store locations. Your task is to analyze the data and provide insights to improve sales performance.
𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝟏:
Using SQL Server, how would you determine the top-selling products for the current month?
𝐀𝐧𝐚𝐥𝐲𝐳𝐞𝟏:
To determine the top-selling products for the current month, I would start by querying the sales transactions table to retrieve all sales made within the current month. I would then join this table with the product table using the product ID to get the product names and group the results by product name while summing up the quantities sold. Finally, I would order the results by the total quantity sold in descending order and limit the output to the top N products.
𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝟐:
How would you analyze customer purchasing behavior to identify potential upsell or cross-sell opportunities?
𝐀𝐧𝐚𝐥𝐲𝐳𝐞 𝟐:
To analyze customer purchasing behavior and identify upsell or cross-sell opportunities, I would examine the sales transactions table and look for patterns in customer buying habits. This could involve identifying frequently co-purchased products or analyzing the average order value per customer. Additionally, I might segment customers based on their purchase history, demographics, or other relevant factors to tailor specific upsell or cross-sell strategies.
𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝟑:
How would you assess the performance of different store locations in terms of sales revenue?
𝐀𝐧𝐚𝐥𝐲𝐳𝐞 𝟑:
To assess the performance of different store locations in terms of sales revenue, I would query the sales transactions table and join it with the store locations table using the store ID. Then, I would group the results by store location and calculate the total sales revenue for each location by summing up the transaction amounts. Finally, I would order the results by sales revenue in descending order to identify the top-performing locations.
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24 𝐓𝐨𝐩 𝐜𝐨𝐦𝐩𝐚𝐧𝐲 𝐢𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐒𝐐𝐋 𝐑𝐞𝐚𝐥 𝐖𝐨𝐫𝐥𝐝 𝐒𝐜𝐞𝐧𝐞𝐫𝐢𝐨:
𝐒𝐜𝐞𝐧𝐞𝐫𝐢𝐨:
You're working as a data analyst for a healthcare provider organization. The organization manages patient data in a SQL Server database, including information about medical appointments, diagnoses, treatments, and patient demographics. Your task is to analyze the data to improve patient care, operational efficiency, and resource allocation.
𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝟒:
How would you identify patients who are at risk of missing their upcoming appointments based on their historical appointment attendance patterns?
𝐀𝐧𝐚𝐥𝐲𝐳𝐞 𝟒:
To identify patients at risk of missing their upcoming appointments based on their historical attendance patterns, I would query the appointments table to retrieve data on past appointments for each patient. Then, I would calculate metrics such as the percentage of attended appointments and the average time between appointments for each patient. Patients with a low attendance rate or irregular appointment intervals could be flagged as at-risk for missing future appointments.
𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝟓:
How would you analyze the effectiveness of different treatments for a specific medical condition based on patient outcomes?
𝐀𝐧𝐚𝐥𝐲𝐳𝐞 𝟓:
To analyze the effectiveness of different treatments for a specific medical condition based on patient outcomes, I would query the treatments table to retrieve data on treatments administered to patients with the target medical condition. Then, I would join this data with patient outcome data, such as recovery status or symptom improvement, and possibly include factors like treatment duration or dosage. Statistical analysis techniques, such as comparing mean outcomes across treatment groups or conducting regression analysis, could be used to assess treatment effectiveness.
𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝟔:
How would you analyze patient demographics to identify disparities in healthcare access or outcomes?
𝐀𝐧𝐚𝐥𝐲𝐳𝐞 𝟔:
To analyze patient demographics and identify disparities in healthcare access or outcomes, I would query the patients table to retrieve demographic information such as age, gender, ethnicity, and socioeconomic status. Then, I would analyze this data in conjunction with healthcare utilization metrics, such as frequency of medical visits, prevalence of chronic conditions, or adherence to treatment plans. Statistical tests, such as chi-square tests or regression analysis, could be used to identify significant differences in healthcare access or outcomes across demographic groups.
Here you can find essential SQL Interview Resources👇
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25 Here is the solution of last post:
1.Scenerio solution - LEFT JOIN Used:
In this scenario, we will use a LEFT JOIN to retrieve all records from the "employees" table and only the matching records from the "departments" table.
SQL Query:
SELECT employees.*, departments.name AS department_name
FROM employees
LEFT JOIN departments ON employees.department_id = departments.id;
2.Scenerio solution - LEFT JOIN Used:
In this scenario, we will use a LEFT JOIN to retrieve all records from the "orders" table and only the matching records from the "customers" table.
SELECT orders.*, customers.name, customers.email
FROM orders
LEFT JOIN customers ON orders.customer_id = customers.customer_id;
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26 Basic Concepts for Data Analyst (SQL)
𝐒𝐜𝐞𝐧𝐞𝐫𝐢𝐨 𝐰𝐢𝐭𝐡 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧 𝐟𝐨𝐫 𝐉𝐨𝐢𝐧𝐬
1.𝐒𝐜𝐞𝐧𝐞𝐫𝐢𝐨:
Let's say we have two tables, "employees" and "departments". The "employees" table contains information about employees such as their ID, name, department ID, and salary. The "departments" table contains information about departments including their ID and name.
We want to retrieve a list of all employees along with the department they belong to, including those employees who are not currently assigned to any department.
2.𝐒𝐜𝐞𝐧𝐞𝐫𝐢𝐨:
Consider two tables, "orders" and "customers". The "orders" table contains information about orders placed by customers, including order ID, customer ID, and order date. The "customers" table contains information about customers, including customer ID, name, and email.
We want to retrieve a list of all orders along with the details of the customers who placed those orders, including orders without corresponding customer records.
𝕋𝕣𝕪 𝕥𝕠 𝕥𝕙𝕚𝕟𝕜 𝕠𝕗 𝕒 𝕤𝕠𝕝𝕦𝕥𝕚𝕠𝕟
Like this if you want me to post solution tomorrow
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27 Quick Recap of SQL Concepts
1. What is SQL?
SQL (Structured Query Language) is a standard programming language used for managing and manipulating relational databases.
2. What are the different types of SQL commands?
- Data Definition Language (DDL): Used to define the structure of database objects (CREATE, ALTER, DROP).
- Data Manipulation Language (DML): Used to manipulate data in the database (SELECT, INSERT, UPDATE, DELETE).
- Data Control Language (DCL): Used to control access and permissions on database objects (GRANT, REVOKE).
3. What is a database schema?
A database schema is a logical structure that represents the layout of the database, including tables, columns, relationships, constraints, and indexes.
4. What is a primary key?
A primary key is a unique identifier for each record in a table. It ensures that each row in the table is uniquely identified and helps maintain data integrity.
5. What is a foreign key?
A foreign key is a column or set of columns in one table that references the primary key in another table. It establishes a relationship between the two tables.
6. What is normalization in SQL?
Normalization is the process of organizing data in a database to reduce redundancy and dependency by dividing large tables into smaller tables and defining relationships between them.
7. What is an index in SQL?
An index is a data structure that improves the speed of data retrieval operations on a database table. It allows for faster searching and sorting of data based on specific columns.
8. What is a JOIN in SQL?
A JOIN is used to combine rows from two or more tables based on a related column between them. Common types of JOINs include INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.
9. What is a subquery in SQL?
A subquery is a query nested within another query. It allows you to perform complex queries by using the result of one query as input for another query.
10. What is the difference between SQL and NoSQL databases?
- SQL databases are relational databases that store data in structured tables with predefined schemas, while NoSQL databases are non-relational databases that store data in flexible, schema-less formats.
- SQL databases use SQL for querying and manipulating data, while NoSQL databases use various query languages or APIs.
- SQL databases are suitable for complex queries and transactions, while NoSQL databases are better for handling large volumes of unstructured data and scaling horizontally. | 13 535 | 99 | Loading... |
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30 https://www.linkedin.com/posts/sql-analysts_sql-dataanalyst-activity-7191645969304764416-7UTy?utm_source=share&utm_medium=member_android | 5 971 | 33 | Loading... |
𝑪𝒐𝒎𝒑𝒓𝒆𝒉𝒆𝒏𝒔𝒊𝒗𝒆 𝒓𝒐𝒂𝒅𝒎𝒂𝒑 𝒕𝒐 𝒃𝒆𝒄𝒐𝒎𝒊𝒏𝒈 𝒂 𝒎𝒂𝒔𝒕𝒆𝒓 𝒊𝒏 𝑺𝑸𝑳:
1. 𝑼𝒏𝒅𝒆𝒓𝒔𝒕𝒂𝒏𝒅 𝒕𝒉𝒆 𝑩𝒂𝒔𝒊𝒄𝒔 𝒐𝒇 𝑺𝑸𝑳
𝐀. 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞𝐬
𝐖𝐡𝐚𝐭 𝐢𝐬 𝐚 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞?: Understanding the concept of databases and relational databases.
𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 (𝐃𝐁𝐌𝐒): Learn about different DBMS like MySQL, PostgreSQL, SQL Server, Oracle.
𝐁. 𝐁𝐚𝐬𝐢𝐜 𝐒𝐐𝐋 𝐂𝐨𝐦𝐦𝐚𝐧𝐝𝐬
𝐃𝐚𝐭𝐚 𝐑𝐞𝐭𝐫𝐢𝐞𝐯𝐚𝐥:
𝐒𝐄𝐋𝐄𝐂𝐓: Basic retrieval of data.
𝐖𝐇𝐄𝐑𝐄: Filtering data based on conditions.
𝐎𝐑𝐃𝐄𝐑 𝐁𝐘: Sorting results.
𝐋𝐈𝐌𝐈𝐓: Limiting the number of rows returned.
𝐃𝐚𝐭𝐚 𝐌𝐚𝐧𝐢𝐩𝐮𝐥𝐚𝐭𝐢𝐨𝐧:
𝐈𝐍𝐒𝐄𝐑𝐓: Adding new data.
𝐔𝐏𝐃𝐀𝐓𝐄: Modifying existing data.
𝐃𝐄𝐋𝐄𝐓𝐄: Removing data.
2. 𝐈𝐧𝐭𝐞𝐫𝐦𝐞𝐝𝐢𝐚𝐭𝐞 𝐒𝐐𝐋 𝐒𝐤𝐢𝐥𝐥𝐬
𝐀. 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐃𝐚𝐭𝐚 𝐑𝐞𝐭𝐫𝐢𝐞𝐯𝐚𝐥
𝐉𝐎𝐈𝐍𝐬: Understanding different types of joins (INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN).
𝐀𝐠𝐠𝐫𝐞𝐠𝐚𝐭𝐞 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐬: Using functions like COUNT, SUM, AVG, MIN, MAX.
𝐆𝐑𝐎𝐔𝐏 𝐁𝐘: Grouping data to perform aggregate calculations.
𝐇𝐀𝐕𝐈𝐍𝐆: Filtering groups based on aggregate values.
𝐁. 𝐒𝐮𝐛𝐪𝐮𝐞𝐫𝐢𝐞𝐬 𝐚𝐧𝐝 𝐍𝐞𝐬𝐭𝐞𝐝 𝐐𝐮𝐞𝐫𝐢𝐞𝐬
𝐒𝐮𝐛𝐪𝐮𝐞𝐫𝐢𝐞𝐬: Using queries within queries.
𝐂𝐨𝐫𝐫𝐞𝐥𝐚𝐭𝐞𝐝 𝐒𝐮𝐛𝐪𝐮𝐞𝐫𝐢𝐞𝐬: Subqueries that reference columns from the outer query.
𝑪. 𝑫𝒂𝒕𝒂 𝑫𝒆𝒇𝒊𝒏𝒊𝒕𝒊𝒐𝒏 𝑳𝒂𝒏𝒈𝒖𝒂𝒈𝒆 (𝑫𝑫𝑳)
𝐂𝐫𝐞𝐚𝐭𝐢𝐧𝐠 𝐓𝐚𝐛𝐥𝐞𝐬: CREATE TABLE.
𝐌𝐨𝐝𝐢𝐟𝐲𝐢𝐧𝐠 𝐓𝐚𝐛𝐥𝐞𝐬: ALTER TABLE.
𝑹𝒆𝒎𝒐𝒗𝒊𝒏𝒈 𝑻𝒂𝒃𝒍𝒆𝒔: DROP TABLE.
3. 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐒𝐐𝐋 𝐓𝐞𝐜𝐡𝐧𝐢𝐪𝐮𝐞𝐬
𝐀. 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧
𝐈𝐧𝐝𝐞𝐱𝐞𝐬: Understanding and creating indexes to speed up queries.
𝐐𝐮𝐞𝐫𝐲 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Techniques to write efficient SQL queries.
𝐁. 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐒𝐐𝐋 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐬
𝐖𝐢𝐧𝐝𝐨𝐰 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐬: Using functions like ROW_NUMBER, RANK, DENSE_RANK, LEAD, LAG.
𝐂𝐓𝐄 (𝐂𝐨𝐦𝐦𝐨𝐧 𝐓𝐚𝐛𝐥𝐞 𝐄𝐱𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧𝐬): Using WITH to create temporary result sets.
𝐂. 𝐓𝐫𝐚𝐧𝐬𝐚𝐜𝐭𝐢𝐨𝐧𝐬 𝐚𝐧𝐝 𝐂𝐨𝐧𝐜𝐮𝐫𝐫𝐞𝐧𝐜𝐲
𝐓𝐫𝐚𝐧𝐬𝐚𝐜𝐭𝐢𝐨𝐧𝐬: Using BEGIN, COMMIT, ROLLBACK.
𝐂𝐨𝐧𝐜𝐮𝐫𝐫𝐞𝐧𝐜𝐲 𝐂𝐨𝐧𝐭𝐫𝐨𝐥: Understanding isolation levels and locking mechanisms.
4. 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐚𝐥 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐚𝐧𝐝 𝐑𝐞𝐚𝐥-𝐖𝐨𝐫𝐥𝐝 𝐒𝐜𝐞𝐧𝐚𝐫𝐢𝐨𝐬
𝐀. 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐃𝐞𝐬𝐢𝐠𝐧
𝐍𝐨𝐫𝐦𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Understanding normal forms and how to normalize databases.
𝐄𝐑 𝐃𝐢𝐚𝐠𝐫𝐚𝐦𝐬: Creating Entity-Relationship diagrams to model databases.
𝐁. 𝐃𝐚𝐭𝐚 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧
𝐄𝐓𝐋 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐞𝐬: Extract, Transform, Load processes for data integration.
𝐒𝐭𝐨𝐫𝐞𝐝 𝐏𝐫𝐨𝐜𝐞𝐝𝐮𝐫𝐞𝐬 𝐚𝐧𝐝 𝐓𝐫𝐢𝐠𝐠𝐞𝐫𝐬: Writing and using stored procedures and triggers for complex logic and automation.
𝐂. 𝐂𝐚𝐬𝐞 𝐒𝐭𝐮𝐝𝐢𝐞𝐬 𝐚𝐧𝐝 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬
𝐑𝐞𝐚𝐥-𝐖𝐨𝐫𝐥𝐝 𝐒𝐜𝐞𝐧𝐚𝐫𝐢𝐨𝐬: Work on case studies involving complex database operations.
𝐂𝐚𝐩𝐬𝐭𝐨𝐧𝐞 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬: Develop comprehensive projects that showcase your SQL expertise.
𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞𝐬 𝐚𝐧𝐝 𝐓𝐨𝐨𝐥𝐬
𝐁𝐨𝐨𝐤𝐬: "SQL in 10 Minutes, Sams Teach Yourself" by Ben Forta, "SQL for Data Scientists" by Renee M. P. Teate.
𝐎𝐧𝐥𝐢𝐧𝐞 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬: Coursera, Udacity, edX, Khan Academy.
𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬: LeetCode, HackerRank, Mode Analytics, SQLZoo.
Like for more
Here you can find quick SQL Revision Notes👇
https://topmate.io/analyst/864817
Hope it helps :)
👍 4❤ 1
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SQL Overview
Database overview
Basic Datatypes
Retrieval of Data
(Select, From, Where ,
Distinct, order By)
Working with Operators
BODMAS Rule (working
with multiple operators)
Basic SQL functions
Wildcard
Concept of Null
Practice examples
Group By
Having vs Where
Aggregate Functions
DDL vs DML
Create, Insert, Update,
Delete, Drop, Alter,
Truncate
Joins – Understanding
and working with Joins
Subqueries
Practice examples and
QUIZ
Introduction to Advanced
SQL
Introduction to Snowflake Cloud
SQL - Basics to Intermediate [LIVE session] with Snowflake Learning
Software Instructor
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Top 10 SQL concepts for data analysts
1. Database: A database is a structured collection of data that is organized and managed for easy access and retrieval. It stores data in tables, which are made up of rows and columns.
2. SQL (Structured Query Language): SQL is a programming language used to communicate with and manipulate databases. It allows data analysts to retrieve, insert, update, and delete data from a database.
3. Tables: Tables are the basic building blocks of a database. They consist of rows (records) and columns (fields) that store data in a structured format.
4. Queries: Queries are SQL statements used to retrieve specific data from a database. They can be simple or complex, involving multiple tables and conditions.
5. Joins: Joins are used to combine data from multiple tables based on a common field. They allow data analysts to retrieve related information from different tables in a single query.
6. Aggregation Functions: Aggregation functions, such as SUM, COUNT, AVG, MIN, and MAX, are used to perform calculations on groups of data. They are commonly used to summarize and analyze large datasets.
7. Filtering: Filtering allows data analysts to retrieve specific data based on certain conditions. It involves using the WHERE clause in SQL queries to specify the criteria for selecting records.
8. Sorting: Sorting allows data analysts to arrange data in a specific order. It involves using the ORDER BY clause in SQL queries to sort records based on one or more columns.
9. Subqueries: Subqueries are queries nested within another query. They allow data analysts to perform complex operations by using the results of one query as input for another query.
10. Data Manipulation Language (DML): DML statements, such as INSERT, UPDATE, and DELETE, are used to modify data in a database. Data analysts use these statements to insert new records, update existing records, or delete unwanted records.
Here you can find quick SQL Revision Notes👇
https://topmate.io/analyst/864817
Hope it helps :)
👍 20❤ 6
📊🚀A beginner's roadmap for learning SQL:
🔹Understand Basics:
Learn what SQL is and its purpose in managing relational databases.
Understand basic database concepts like tables, rows, columns, and relationships.
🔹Learn SQL Syntax:
Familiarize yourself with SQL syntax for common commands like SELECT, INSERT, UPDATE, DELETE.
Understand clauses like WHERE, ORDER BY, GROUP BY, and JOIN.
🔹Setup a Database:
Install a relational database management system (RDBMS) like MySQL, SQLite, or PostgreSQL.
Practice creating databases, tables, and inserting data.
🔹Retrieve Data (SELECT):
Learn to retrieve data from a database using SELECT statements.
Practice filtering data using WHERE clause and sorting using ORDER BY.
🔹Modify Data (INSERT, UPDATE, DELETE):
Understand how to insert new records, update existing ones, and delete data.
Be cautious with DELETE to avoid unintentional data loss.
🔹Working with Functions:
Explore SQL functions like COUNT, AVG, SUM, MAX, MIN for data analysis.
Understand string functions, date functions, and mathematical functions.
🔹Data Filtering and Sorting:
Learn advanced filtering techniques using AND, OR, and IN operators.
Practice sorting data using multiple columns.
🔹Table Relationships (JOIN):
Understand the concept of joining tables to retrieve data from multiple tables.
Learn about INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.
🔹Grouping and Aggregation:
Explore GROUP BY clause to group data based on specific columns.
Understand aggregate functions for summarizing data (SUM, AVG, COUNT).
🔹Subqueries:
Learn to use subqueries to perform complex queries.
Understand how to use subqueries in SELECT, WHERE, and FROM clauses.
🔹Indexes and Optimization:
Gain knowledge about indexes and their role in optimizing queries.
Understand how to optimize SQL queries for better performance.
🔹Transactions and ACID Properties:
Learn about transactions and the ACID properties (Atomicity, Consistency, Isolation, Durability).
Understand how to use transactions to maintain data integrity.
🔹Normalization:
Understand the basics of database normalization to design efficient databases.
Learn about 1NF, 2NF, 3NF, and BCNF.
🔹Backup and Recovery:
Understand the importance of database backups.
Learn how to perform backups and recovery operations.
🔹Practice and Projects:
Apply your knowledge through hands-on projects.
Practice on platforms like LeetCode, HackerRank, or build your own small database-driven projects.
👀👍Remember to practice regularly and build real-world projects to reinforce your learning. Happy coding!
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Complete topics & subtopics of hashtag#SQL for Data Engineer role:-
𝟭. 𝗕𝗮𝘀𝗶𝗰 𝗦𝗤𝗟 𝗦𝘆𝗻𝘁𝗮𝘅:
SQL keywords
Data types
Operators
SQL statements (SELECT, INSERT, UPDATE, DELETE)
𝟮. 𝗗𝗮𝘁𝗮 𝗗𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 (𝗗𝗗𝗟):
CREATE TABLE
ALTER TABLE
DROP TABLE
Truncate table
𝟯. 𝗗𝗮𝘁𝗮 𝗠𝗮𝗻𝗶𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 (𝗗𝗠𝗟):
SELECT statement (SELECT, FROM, WHERE, ORDER BY, GROUP BY, HAVING, JOINs)
INSERT statement
UPDATE statement
DELETE statement
𝟰. 𝗔𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗲 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀:
SUM, AVG, COUNT, MIN, MAX
GROUP BY clause
HAVING clause
𝟱. 𝗗𝗮𝘁𝗮 𝗖𝗼𝗻𝘀𝘁𝗿𝗮𝗶𝗻𝘁𝘀:
Primary Key
Foreign Key
Unique
NOT NULL
CHECK
𝟲. 𝗝𝗼𝗶𝗻𝘀:
INNER JOIN
LEFT JOIN
RIGHT JOIN
FULL OUTER JOIN
Self Join
Cross Join
𝟳. 𝗦𝘂𝗯𝗾𝘂𝗲𝗿𝗶𝗲𝘀:
Types of subqueries (scalar, column, row, table)
Nested subqueries
Correlated subqueries
𝟴. 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗦𝗤𝗟 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀:
String functions (CONCAT, LENGTH, SUBSTRING, REPLACE, UPPER, LOWER)
Date and time functions (DATE, TIME, TIMESTAMP, DATEPART, DATEADD)
Numeric functions (ROUND, CEILING, FLOOR, ABS, MOD)
Conditional functions (CASE, COALESCE, NULLIF)
𝟵. 𝗩𝗶𝗲𝘄𝘀:
Creating views
Modifying views
Dropping views
𝟭𝟬. 𝗜𝗻𝗱𝗲𝘅𝗲𝘀:
Creating indexes
Using indexes for query optimization
𝟭𝟭. 𝗧𝗿𝗮𝗻𝘀𝗮𝗰𝘁𝗶𝗼𝗻𝘀:
ACID properties
Transaction management (BEGIN, COMMIT, ROLLBACK, SAVEPOINT)
Transaction isolation levels
𝟭𝟮. 𝗗𝗮𝘁𝗮 𝗜𝗻𝘁𝗲𝗴𝗿𝗶𝘁𝘆 𝗮𝗻𝗱 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆:
Data integrity constraints (referential integrity, entity integrity)
GRANT and REVOKE statements (granting and revoking permissions)
Database security best practices
𝟭𝟯. 𝗦𝘁𝗼𝗿𝗲𝗱 𝗣𝗿𝗼𝗰𝗲𝗱𝘂𝗿𝗲𝘀 𝗮𝗻𝗱 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀:
Creating stored procedures
Executing stored procedures
Creating functions
Using functions in queries
𝟭𝟰. 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻:
Query optimization techniques (using indexes, optimizing joins, reducing subqueries)
Performance tuning best practices
𝟭𝟱. 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗦𝗤𝗟 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀:
Recursive queries
Pivot and unpivot operations
Window functions (Row_number, rank, dense_rank, lead & lag)
CTEs (Common Table Expressions)
Dynamic SQL
Here you can find quick SQL Revision Notes👇
https://topmate.io/analyst/864817
Hope it helps :)