What You’ll Learn
  • Understand basic SQL syntax and structure of SQL statements.
  • Retrieve and manipulate data using SELECT
  • INSERT
  • UPDATE
  • and DELETE commands.
  • Apply aggregate and string functions to process data effectively.
  • Utilize various types of JOINs to combine data from multiple tables.
  • Write subqueries to perform complex queries and data retrieval tasks.
  • Implement indexing strategies to optimize query performance.
  • Manage transactions while ensuring ACID properties are maintained.
  • Design and modify database structures using Data Definition Language (DDL).
  • Create and use stored procedures
  • functions
  • and triggers for automation.
  • Apply best practices in SQL to prevent security vulnerabilities like SQL injection.

Requirements

  • Basic understanding of databases and data management concepts.
  • Familiarity with programming logic will be beneficial but is not mandatory.
  • Willingness to master SQL

Description

This comprehensive practice tests "[NEW] 1500 Master SQL: Interview Questions - Practice Tests" are meticulously designed for learners at all levels—from beginners to advanced practitioners—who aspire to master SQL. Covering a wide array of topics such as basic SQL concepts, functions, joins, transactions, and advanced SQL techniques, this course provides a robust foundation in database management.

These practice tests cover:

1. Basic SQL Concepts

  • SQL Syntax: Understanding the structure of basic SQL statements.

  • SELECT Queries: Retrieving data from databases.

  • INSERT, UPDATE, DELETE: Modifying and deleting records in tables.

  • WHERE Clause: Filtering data based on conditions.

  • ORDER BY, GROUP BY: Sorting and grouping results.

2. SQL Functions

  • Aggregate Functions: COUNT(), SUM(), AVG(), MIN(), MAX().

  • String Functions: CONCAT(), LENGTH(), SUBSTRING(), UPPER(), LOWER().

  • Date Functions: NOW(), CURDATE(), DATEADD(), DATEDIFF().

  • Mathematical Functions: ROUND(), CEIL(), FLOOR().

  • Conditional Functions: CASE, IF().

3. Joins and Relationships

  • INNER JOIN: Fetching rows with matching values in both tables.

  • LEFT JOIN (LEFT OUTER JOIN): Fetching all rows from the left table, with matching rows from the right.

  • RIGHT JOIN (RIGHT OUTER JOIN): Fetching all rows from the right table, with matching rows from the left.

  • FULL OUTER JOIN: Fetching rows where there is a match in one of the tables.

  • Self Join: Joining a table with itself.

  • Cross Join: Cartesian product of two tables.

  • Equi-join and Non-Equi Join.

4. Subqueries

  • Single-row Subqueries: Queries returning a single row.

  • Multi-row Subqueries: Queries returning multiple rows.

  • Correlated Subqueries: A subquery that references columns from the outer query.

  • EXISTS, NOT EXISTS: Checking the existence of records.

  • IN, NOT IN: Checking values within a set of values.

5. Indexes and Performance Tuning

  • Types of Indexes: Clustered vs. Non-clustered Indexes.

  • Creating and Dropping Indexes: CREATE INDEX, DROP INDEX.

  • Impact of Indexes on Query Performance: When to use indexes, avoiding index overuse.

  • EXPLAIN/EXPLAIN PLAN: Understanding query execution plans.

  • Query Optimization Techniques: Avoiding full table scans, reducing joins, etc.

6. Transactions and ACID Properties

  • Transaction Control Statements: BEGIN, COMMIT, ROLLBACK, SAVEPOINT.

  • ACID Properties: Atomicity, Consistency, Isolation, Durability.

  • Isolation Levels: Read Uncommitted, Read Committed, Repeatable Read, Serializable.

  • Concurrency Control: Locking mechanisms, deadlocks, and how to avoid them.

7. Data Definition Language (DDL)

  • CREATE, ALTER, DROP: Creating and modifying tables and indexes.

  • Constraints: Primary Key, Foreign Key, Unique, Check, Default, and Not Null.

  • Normalization: First Normal Form (1NF), Second Normal Form (2NF), Third Normal Form (3NF), Boyce-Codd Normal Form (BCNF).

  • Denormalization: Understanding when and why to denormalize.

8. Data Manipulation Language (DML)

  • INSERT: Inserting data into tables.

  • UPDATE: Modifying existing records.

  • DELETE vs TRUNCATE: Differences and use cases.

  • MERGE: Combining insert, update, and delete operations in one statement.

9. Data Control Language (DCL)

  • GRANT: Giving users permissions.

  • REVOKE: Removing permissions.

  • User Roles and Privileges: Role-based access control in databases.

10. Stored Procedures, Functions, and Triggers

  • Stored Procedures: Writing and executing stored procedures.

  • Functions: Creating and using user-defined functions.

  • Triggers: Automating actions with triggers (e.g., BEFORE INSERT, AFTER UPDATE).

11. Views

  • Creating Views: Simplifying complex queries using views.

  • Updatable Views: Conditions where a view can be updated.

  • Materialized Views: Using materialized views for performance optimization.

12. Temporary Tables and CTEs

  • Temporary Tables: Creating and using temporary tables.

  • Common Table Expressions (CTEs): Recursive and non-recursive CTEs for simplifying queries.

13. Handling Nulls

  • IS NULL, IS NOT NULL: Handling null values in queries.

  • NULL Functions: COALESCE(), NULLIF().

14. SQL Best Practices

  • SQL Injection Prevention: Writing secure SQL queries.

  • Query Efficiency: Writing readable and efficient SQL.

  • Batch Processing: Handling bulk operations efficiently.

  • Using Parameters: Safely including user inputs.

15. Advanced SQL Concepts

  • Window Functions: ROW_NUMBER(), RANK(), DENSE_RANK(), NTILE(), LAG(), LEAD().

  • Partitioning: Horizontal partitioning (partition by range, list, etc.).

  • Data Warehousing Queries: Fact tables, dimension tables, star schema, snowflake schema.

  • Pivot and Unpivot: Transposing data in SQL.

  • Recursive Queries: Using recursion in CTEs.

  • JSON and XML Handling: Working with JSON/XML data types in SQL.

16. Database Design

  • Entity-Relationship Model: Defining entities, relationships, and keys.

  • Normalization vs. Denormalization: Deciding when to normalize or denormalize for performance.

  • Relational vs. NoSQL Databases: Understanding differences between SQL and NoSQL.

Participants will engage in extensive practice tests that simulate real-world scenarios and interview questions commonly asked by employers. Each section is structured to build upon the previous one, ensuring a gradual increase in complexity that allows learners to develop their skills systematically.

Throughout the course, students will explore essential topics including data retrieval using SELECT statements, data manipulation with INSERT/UPDATE/DELETE commands, the intricacies of JOIN operations, and the application of aggregate functions. Additionally, learners will gain insights into performance tuning through indexing and transaction management while adhering to ACID properties.

By the end of this course, participants will not only be well-prepared for technical interviews but also equipped with practical skills applicable in any data-driven role.

Join us now and take your first step towards becoming an SQL expert! Enroll today and unlock your potential in the world of databases!

Who this course is for:

  • Anyone interested in learning and mastering SQL
  • from complete beginners to those with some experience looking to deepen their understanding
  • Valuable for individuals aiming for roles in data analysis
  • software development
  • database administration
  • or quality assurance.
  • Learners who want to confidently tackle SQL interview questions and real-world database challenges.
Courses

Course Includes:

  • Price: FREE
  • Enrolled: 12 students
  • Language: English
  • Certificate: Yes

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