SQL — Beginner to Super Advanced
Master SQL for analytics, engineering, and large-scale data systems. Hands-on labs across PostgreSQL, MySQL, SQL Server, Snowflake, BigQuery, Databricks SQL, ClickHouse and more. Learn query writing, window functions, performance tuning, execution plans, indexing, partitioning, OLAP/OLTP design, and distributed SQL best practices.
Program Snapshot
- • Levels: Beginner, Advanced, Expert, Super Advanced
- • Engines: PostgreSQL, MySQL, SQL Server, Snowflake, BigQuery, Databricks SQL, ClickHouse
- • Focus: Analytics, Data Engineering, Performance, Distributed SQL
- • Deliverables: Lab repos, query cookbook, optimization playbooks
Why this course
SQL is the lingua franca of data. This program takes learners from writing correct queries to designing high-performance data platforms and tuning queries across different engines. It's structured so non-engineers can become power users and engineers can gain DBA-level performance skills.
Audience
Analysts, data engineers, DBAs, backend developers, and architects who work with relational and analytic databases.
Outcomes
Write complex analytics queries, tune high-volume workloads, design warehouses, and operate distributed SQL engines.
Prerequisites
Beginner track requires no SQL experience. Advanced tracks assume familiarity with basic SELECT/JOIN concepts.
Progression Levels
Structured certificates at four levels — each with exams, labs, and a capstone aligned to real-world domains.
Level 1 — Beginner
SQL basics: SELECT, FILTER, JOINs, GROUP BY, simple aggregations, basic window functions and CTEs.
- Labs: Sales & orders dataset queries
- Quiz: 40-question multiple choice
Level 2 — Advanced
Advanced window functions, analytic patterns, complex joins, subqueries, performance-aware SQL, and materialized views.
- Labs: Cohort analysis, LAG/LEAD patterns
- Assessment: Practical query assignment
Level 3 — Expert
Execution plans, indexing strategies, partitions, transactions, concurrency, stored procedures, and query refactoring.
- Labs: Optimize queries on 50M+ rows, index design
- Assessment: Performance tuning project
Level 4 — Super Advanced
Distributed SQL architectures, cost-based optimization internals, query federation, columnar engines (ClickHouse), OLAP design, and cloud-specific tuning (Snowflake/BigQuery).
- Labs: Data warehouse design, partition strategies, materialized views at scale
- Assessment: Capstone — design & deliver a performant data mart
Curriculum Highlights — Topics & Modules
Below are representative modules. The full syllabus maps modules to levels and engines (Postgres, Snowflake, BigQuery, ClickHouse, Databricks SQL).
Analytical SQL & BI Patterns
- Window functions, running totals, moving averages
- Time-series aggregation, time bucketing, fiscal calendars
- CTEs for pipeline clarity and modular queries
- Query patterns for cohort, retention and funnel analysis
Data Engineering SQL
- ETL vs ELT patterns, incremental loads, CDC basics
- Materialized views, partitions, clustering, and micro-partitions
- Scheduling, orchestration with Airflow / dbt integration
- Data quality checks and testable SQL patterns
Performance & Tuning
- Indexes (B-tree, GIN, BRIN), predicate pushdown, and statistics
- Execution plans, cardinality estimation, and common pitfalls
- Batching, pagination, and avoiding anti-patterns (SELECT *)
- Concurrency control, isolation levels, and locking
Distributed & Cloud SQL
- Snowflake micro-partitioning, BigQuery slots & cost controls
- Databricks SQL optimizations and adaptive query execution
- ClickHouse columnar engine, MergeTree tables, and OLAP patterns
- Federated queries, external tables, and cross-engine considerations
Security & Governance
- Roles & privileges, row-level security, and data access controls
- Data lineage, auditing, and SQL-based masking techniques
- Cost governance and query throttling strategies
Tooling & Observability
- EXPLAIN/EXPLAIN ANALYZE, async profilers, and query logs
- Monitoring slow queries, tracking cost and usage metrics
- dbt models, lineage visualization, and CI for SQL tests
Hands-on Labs & Domain Case Studies
Real datasets and domain-specific labs to apply SQL skills. Each lab includes test datasets, starter queries, and a checklist for optimization and production readiness.
Banking — Transaction Analytics & AML
Aggregate transactions, compute rolling customer risk scores, detect anomalies, and build efficient alert queries for AML workflows (includes time-windowed joins and stateful aggregations).
Retail — Funnels, CLV & Promotion Analysis
Sessionization, funnel conversion rates, cohort CLV, and measuring promo uplift with proper control/baseline SQL patterns.
Energy — Time-Series Aggregation
Handle high-volume time-series data, compute load curves, resample irregular telemetry, and optimize windowed queries for performance.
Healthcare — Claims & Population Metrics
Process EHR/claims-like datasets, build patient cohorts, and compute population-level metrics while preserving privacy via masking and aggregation.
Supported Engines & Engine-specific Tips
We teach engine-agnostic SQL principles and deep dives into popular platforms so you can transfer skills across systems.
PostgreSQL / MySQL / SQL Server
Indexes, explain plans, stored procedures, window functions, and OLTP tuning. Includes platform-specific tips (VACUUM, autovacuum, statistics).
Snowflake & BigQuery
Micro-partitions, clustering keys (Snowflake), slot management (BigQuery), cost control, and best practices for ELT workflows and materialized views.
Databricks SQL & ClickHouse
Databricks adaptive execution, cache strategies, and ClickHouse MergeTree engines, indexing, and OLAP optimizations for extremely high-throughput queries.
Deliverables & Certification
- Tiered certifications: Yukti SQL Certified — Beginner / Advanced / Expert / Super Advanced
- Hands-on lab repos, solution sets, and an optimized query cookbook
- Capstone: a deployable data mart or analytics pipeline with performance report
- Playbooks: Indexing guide, partitioning checklist, and engine-specific tuning notes
Pricing & Delivery Options
Beginner (Level 1)
Self-paced modules, beginner labs and Level 1 assessment.
Advanced (Level 2)
Includes Level 1 content plus advanced analytics and BI labs.
Expert (Level 3)
Performance tuning, execution plans, and large-scale optimization labs.
Super Advanced (Level 4)
Full comprehensive bundle with distributed SQL, warehouse design, capstone and extended mentorship.
Enroll / Request Brochure
Choose your level and tell us about your goals — we will reply with a tailored syllabus, cohort dates, and sandbox access details.