Crack SQL Interview : 200+ Questions with Concept Building

Crack SQL Interview : 200+ Questions with Concept Building | Udemy [Update 06/2024]
English | Size: 13.2 GB
Genre: eLearning

The Ultimate Course for cracking Interviews with SQL Questions. The course cover basic to advance level question

What you’ll learn
Basic to advanced SQL query writing
Joins and subqueries
Normalization and denormalization
Entity-Relationship Diagrams (ERDs)
Indexing and performance optimization
Window functions
Common Table Expressions (CTEs)
Stored procedures and functions
Triggers and events
Aggregations and grouping
Query optimization
Problem-solving techniques
Explaining complex queries
Whiteboarding SQL solutions
Data preparation and cleaning
Security and access control

Course Objective: Master SQL for technical interviews and enhance database proficiency

Target Audience: Data Engineers, Analysts, Scientists, Software Engineers, DBAs, and aspiring data professionals

Key Learning Areas:

Foundational to advanced SQL concepts

Complex query writing and optimization

Database design principles

Performance tuning techniques

Practical Focus:

Real-world SQL problem-solving

Hands-on exercises and case studies

Mock interview scenarios

Topics Covered:

Data manipulation (SELECT, INSERT, UPDATE, DELETE)

Join operations and subqueries

Window functions and Common Table Expressions (CTEs)

Query optimization and execution plan analysis

Skills Development:

Efficient problem-solving approaches

Clear articulation of SQL solutions

Whiteboarding complex queries

Career Benefits:

Confidence in technical interviews

Enhanced SQL proficiency for various data roles

Competitive edge in the job market

Learning Outcomes:

Ability to tackle complex SQL challenges

Improved database performance optimization skills

Effective communication of database concepts

Course Delivery: Blend of theoretical instruction and practical application

Final Goal: Prepare students to excel in SQL-focused technical interviews and advance their careers in the data industry

Topics Covered in the Course:

1. SQL Fundamentals

Basic SQL syntax and structure

SELECT statements and data retrieval

Filtering with WHERE clauses

Sorting results with ORDER BY

Limiting result sets

2. Data Manipulation

INSERT statements for adding data

UPDATE statements for modifying existing data

DELETE statements for removing data

MERGE statements for upserts

3. Table Operations

CREATE TABLE syntax and best practices

ALTER TABLE for modifying table structures

DROP and TRUNCATE operations

Temporary tables and their uses

4. Joins and Relationships

INNER, LEFT, RIGHT, and FULL OUTER JOINs

Self-joins and their applications

CROSS JOINs and Cartesian products

Handling NULL values in joins

5. Subqueries and Nested Queries

Correlated and non-correlated subqueries

Subqueries in SELECT, FROM, and WHERE clauses

EXISTS and NOT EXISTS operations

Comparing subquery results with ANY and ALL

6. Aggregation and Grouping

Aggregate functions (SUM, AVG, COUNT, etc.)

GROUP BY clauses for data summarization

HAVING clauses for filtering grouped data

Dealing with NULL values in aggregations

7. Advanced SQL Techniques

Window functions for analytics

Common Table Expressions (CTEs) for query readability

Recursive CTEs for hierarchical data

Pivoting and unpivoting data

8. Data Types and Functions

Understanding and using various SQL data types

Date and time functions

String manipulation functions

Numeric and mathematical functions

Conditional expressions (CASE statements)

9. Indexes and Performance Tuning

Creating and using indexes effectively

Understanding query execution plans

Identifying and resolving performance bottlenecks

Statistics and their impact on query optimization

10. Transactions and Concurrency

ACID properties of transactions

Transaction isolation levels

Handling deadlocks and race conditions

Optimistic vs. pessimistic locking

11. Views and Stored Procedures

Creating and managing views

Materialized views for performance

Writing and optimizing stored procedures

Functions vs. stored procedures

12. Database Design Principles

Normalization and denormalization techniques

Entity-Relationship Diagrams (ERDs)

Primary and foreign key constraints

Maintaining data integrity

13. Security and Access Control

User authentication and authorization

Role-based access control

Row-level and column-level security

Auditing database activities

14. Handling Large Datasets

Partitioning strategies for big tables

Batch processing techniques

Optimizing queries for large-scale data

Indexing strategies for big data

15. SQL in Data Analysis

Writing complex analytical queries

Cohort analysis techniques

Time series analysis in SQL

A/B testing with SQL

16. Interview Strategies

Approaching and breaking down complex SQL problems

Optimizing queries on the fly

Explaining your thought process effectively

Handling ambiguous requirements in interview questions

Each topic is covered in-depth with practical examples, real-world scenarios, and interview-style questions to ensure comprehensive understanding and application.

Who this course is for:
This course is designed for professionals and aspiring candidates in data-related fields who are preparing for technical interviews or seeking to enhance their SQL skills.
The primary audience includes: Data Engineers
Professionals responsible for designing, building, and maintaining data pipelines and infrastructure.
Data Analysts: Individuals who work with data to provide insights and support decision-making processes.
Data Scientists: Professionals who use statistical and machine learning techniques to analyze complex data sets.
Software Engineers: Developers who work on applications that interact with databases and require SQL knowledge.
Database Administrators (DBAs): Specialists responsible for the performance, integrity, and security of databases.
Business Intelligence Analysts: Professionals who use data to drive business strategy and decision-making.
Recent Graduates: Those with a background in computer science, information systems, or related fields looking to start their career in data-driven roles.
Career Changers: Individuals transitioning into data-related roles from other fields.
IT Professionals: Those looking to expand their skill set to include database management and SQL proficiency.
Students: Upper-level undergraduate or graduate students in computer science, data science, or related programs preparing for internships or entry-level positions. This course is suitable for beginners with basic SQL knowledge looking to advance their skills, as well as experienced professionals aiming to refine their expertise and prepare for challenging interview questions in the data industry.

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