Database Engineering & Data Systems Topics
Database design patterns, optimization, scaling strategies, storage technologies, data warehousing, and operational database management. Covers database selection criteria, query optimization, replication strategies, distributed databases, backup and recovery, and performance tuning at database layer. Distinct from Systems Architecture (which addresses service-level distribution) and Data Science (which addresses analytical approaches).
Aggregation and Grouping
Covers SQL grouping and aggregation concepts used to summarize data across rows. Key skills include using GROUP BY with aggregate functions such as COUNT, SUM, AVG, MIN, and MAX, counting distinct values, and filtering grouped results with HAVING while understanding the difference between WHERE and HAVING. Candidates should demonstrate correct handling of NULL values in aggregates, grouping by expressions and multiple columns, and writing multi level aggregations using ROLLUP, CUBE, and GROUPING SETS. Also important is knowing when to use subqueries or common table expressions for intermediate aggregation, the difference between aggregate functions and window functions, and how grouping interacts with joins and data types. Interview questions may test correctness of queries, edge cases, performance considerations such as appropriate indexes and query plans, and the ability to transform business questions like who are the top customers or which categories have declining sales into correct aggregated SQL statements.
SQL Fundamentals and Query Writing
Comprehensive query writing skills from basic to intermediate level. Topics include SELECT and WHERE, joining tables with inner and outer joins, grouping with GROUP BY and filtering groups with HAVING, common aggregation functions such as COUNT SUM AVG MIN and MAX, ORDER BY and DISTINCT, subqueries and common table expressions, basic window functions such as ROW_NUMBER and RANK, union operations, and principles of readable and maintainable query composition. Also covers basic query execution awareness and common performance pitfalls and how to write correct, efficient queries for combining and summarizing relational data.