Crack Sql Interview – 200+ Questions With Concept Building

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
Requirements
No Programming Experience is Required
Description
Course Objective: Master SQL for technical interviews and enhance database proficiencyTarget Audience: Data Engineers, Analysts, Scientists, Software Engineers, DBAs, and aspiring data professionalsKey Learning Areas:Foundational to advanced SQL conceptsComplex query writing and optimizationDatabase design principlesPerformance tuning techniquesPractical Focus:Real-world SQL problem-solvingHands-on exercises and case studiesMock interview scenariosTopics Covered:Data manipulation (SELECT, INSERT, UPDATE, DELETE)Join operations and subqueriesWindow functions and Common Table Expressions (CTEs)Query optimization and execution plan analysisSkills Development:Efficient problem-solving approachesClear articulation of SQL solutionsWhiteboarding complex queriesCareer Benefits:Confidence in technical interviewsEnhanced SQL proficiency for various data rolesCompetitive edge in the job marketLearning Outcomes:Ability to tackle complex SQL challengesImproved database performance optimization skillsEffective communication of database conceptsCourse Delivery: Blend of theoretical instruction and practical applicationFinal Goal: Prepare students to excel in SQL-focused technical interviews and advance their careers in the data industryTopics Covered in the Course:1. SQL FundamentalsBasic SQL syntax and structureSELECT statements and data retrievalFiltering with WHERE clausesSorting results with ORDER BYLimiting result sets2. Data ManipulationINSERT statements for adding dataUPDATE statements for modifying existing dataDELETE statements for removing dataMERGE statements for upserts3. Table OperationsCREATE TABLE syntax and best practicesALTER TABLE for modifying table structuresDROP and TRUNCATE operationsTemporary tables and their uses4. Joins and RelationshipsINNER, LEFT, RIGHT, and FULL OUTER JOINsSelf-joins and their applicationsCROSS JOINs and Cartesian productsHandling NULL values in joins5. Subqueries and Nested QueriesCorrelated and non-correlated subqueriesSubqueries in SELECT, FROM, and WHERE clausesEXISTS and NOT EXISTS operationsComparing subquery results with ANY and ALL6. Aggregation and GroupingAggregate functions (SUM, AVG, COUNT, etc.)GROUP BY clauses for data summarizationHAVING clauses for filtering grouped dataDealing with NULL values in aggregations7. Advanced SQL TechniquesWindow functions for analyticsCommon Table Expressions (CTEs) for query readabilityRecursive CTEs for hierarchical dataPivoting and unpivoting data8. Data Types and FunctionsUnderstanding and using various SQL data typesDate and time functionsString manipulation functionsNumeric and mathematical functionsConditional expressions (CASE statements)9. Indexes and Performance TuningCreating and using indexes effectivelyUnderstanding query execution plansIdentifying and resolving performance bottlenecksStatistics and their impact on query optimization10. Transactions and ConcurrencyACID properties of transactionsTransaction isolation levelsHandling deadlocks and race conditionsOptimistic vs. pessimistic locking11. Views and Stored ProceduresCreating and managing viewsMaterialized views for performanceWriting and optimizing stored proceduresFunctions vs. stored procedures12. Database Design PrinciplesNormalization and denormalization techniquesEntity-Relationship Diagrams (ERDs)Primary and foreign key constraintsMaintaining data integrity13. Security and Access ControlUser authentication and authorizationRole-based access controlRow-level and column-level securityAuditing database activities14. Handling Large DatasetsPartitioning strategies for big tablesBatch processing techniquesOptimizing queries for large-scale dataIndexing strategies for big data15. SQL in Data AnalysisWriting complex analytical queriesCohort analysis techniquesTime series analysis in SQLA/B testing with SQL16. Interview StrategiesApproaching and breaking down complex SQL problemsOptimizing queries on the flyExplaining your thought process effectivelyHandling ambiguous requirements in interview questionsEach topic is covered in-depth with practical examples, real-world scenarios, and interview-style questions to ensure comprehensive understanding and application.
Overview
Section 1: Week 1
Lecture 1 Foundation Session 1
Lecture 2 Foundation Session 2
Section 2: Questions Booklet 1
Lecture 3 Assignments
Section 3: Week 2
Lecture 4 Session 3
Lecture 5 Session 4
Section 4: Questions Booklet 2
Lecture 6 Questions
Section 5: Week 3
Lecture 7 Session 5
Lecture 8 Session 6
Section 6: Question Booklet 3
Lecture 9 Question
Section 7: Week 4
Lecture 10 Session 7
Section 8: Week 5
Lecture 11 Session 9
Lecture 12 Session 10
Section 9: Week 6
Lecture 13 Session 11
Lecture 14 Session 12
Section 10: Week 7
Lecture 15 Session 13
Lecture 16 Session 14
Lecture 17 Session 15
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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