Confident data changes - You will learn how to insert, update, and delete data safely in more complex scenarios, so you can prepare reliable table operations faster in both test and production environments.
Better reports and summaries - You will master GROUP BY, aggregate functions, and HAVING, enabling you to build clear reports with totals, averages, counts, and trends without manual processing outside the database.
Effective subquery usage - You will use subqueries in WHERE and FROM with much more confidence, including IN and EXISTS, so you can create precise filters and comparisons across multiple data sources.
Faster query performance - You will learn how to create indexes, read execution plans, and spot bottlenecks, which will help you improve queries running on large tables and reduce unnecessary server load.
Practical view design - You will learn to build views based on joins and subqueries, update data through views, and understand where materialized views can simplify everyday work with database objects.
Confidence with data types - You will gain better control over type conversion, text handling, and advanced data types, helping you avoid errors caused by incompatible formats and incorrect value transformations.
Modern analysis techniques - You will master window functions, set operators, and analytical functions such as LEAD and LAG, so you can build rankings, comparisons, and sequence analysis without awkward workarounds.
Safer database operations - You will understand transactions, concurrency, error handling, roles, and permissions, allowing you to control change risk better, protect sensitive data, and predict multi-user impact.
Modifying larger datasets safely calls for techniques that go beyond basic INSERT, UPDATE, and DELETE statements. Participants use INSERT INTO ... SELECT, updates with joins or subqueries, conditional deletes, and MERGE for synchronization, with attention to scalable DML practices.
INSERT INTO ... SELECT,MERGE statement (UPSERT) – data synchronization,GROUP BY and aggregate functions provide the basis for summarizing data, but practical analysis also depends on precise filtering and result shaping. The section combines HAVING, advanced sorting, NULL handling, and conditional expressions such as CASE, COALESCE, and NULLIF.
GROUP BY),COUNT, SUM, AVG, MIN, MAX),HAVING),NULL values,CASE, COALESCE, NULLIF).Complex retrieval often depends on choosing the right relationship between outer queries and intermediate result sets. The section covers correlated and uncorrelated subqueries in SELECT, FROM, and WHERE, operators such as EXISTS or ALL, plus CTEs and recursive CTE patterns.
SELECT, FROM and WHERE clauses,EXISTS, NOT EXISTS, IN, ANY, ALL operators,WITH),When queries slow down, performance work begins with how the engine reads data. Participants examine index impact, create and remove indexes, interpret EXPLAIN or EXPLAIN PLAN output, identify bottlenecks, and tune statements for large datasets using proven efficiency practices.
EXPLAIN, EXPLAIN PLAN),Views help separate data presentation, access control, and query complexity from base tables. This part covers simple and complex view definitions, joins and subqueries inside views, updating data through views, materialized views, and their role in restricting data exposure.
Working across mixed datasets requires careful handling of values and formats. Participants practice type conversion, date and time functions, text processing, and operations on numeric types, with an additional look at JSON data handling where the database engine supports it.
Window functions extend SQL analysis beyond standard aggregation. The section uses OVER with ROW_NUMBER, RANK, DENSE_RANK, NTILE, LEAD, LAG, FIRST_VALUE, and LAST_VALUE, then applies them to running totals, moving averages, and set operators such as UNION or EXCEPT.
OVER),ROW_NUMBER, RANK, DENSE_RANK, NTILE,LEAD and LAG,FIRST_VALUE and LAST_VALUE,UNION, UNION ALL, INTERSECT, EXCEPT).Automating database logic involves more than writing reusable code blocks. The training focuses on stored procedures and user-defined functions, input and output parameters, exception handling, debugging techniques, and the basics of implementing triggers for data-driven actions.
Reliable data changes depend on correct transaction handling and predictable concurrent access. Participants work with BEGIN, COMMIT, and ROLLBACK, compare isolation levels and locking behavior, and learn error-handling approaches that help preserve consistency.
BEGIN, COMMIT, ROLLBACK),Securing database work requires connecting access control with safe coding practices. The section covers roles, user permissions, protection of sensitive data, Dynamic SQL risks, SQL Injection defenses, auditing basics, and rules for designing maintainable SQL code.
Starting from business requirements, participants translate real reporting and operational needs into SQL solutions. They build complex queries with CTEs and window functions, then refine them through execution plan analysis and targeted optimization to solve realistic database problems.
Basic SQL SELECT - You should be comfortable writing simple SELECT queries, choosing columns, filtering with WHERE, and sorting results so you can focus on more advanced techniques during the course.
Simple joins - You should understand how to combine data from at least two tables using basic JOIN clauses, because the later exercises rely on building more complex query structures.
Tables and records - You should understand tables, rows, columns, and keys, and know how to read the structure of a simple database so you can follow the training examples more efficiently.
Basic data modification - You should know the basic use of INSERT, UPDATE, and DELETE in simple cases, so during the training you can focus on applying them in safer and more advanced scenarios.