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).
Marketing Data Model Design
Design efficient data schemas and models to support marketing use cases. Topics include defining entities and relationships such as contacts accounts and events, canonical identifier strategies and identity resolution, trade offs between normalization and denormalization, indexing and partitioning for performance, structured query language query optimization, segmentation and audience building patterns, mapping source fields into canonical schemas, data lineage and auditability, and policies for retention and privacy to support reporting and activation.
Database Fundamentals and SQL Literacy
Core relational database concepts and basic SQL literacy. Covers database objects such as tables, rows, and columns, primary keys and foreign keys, relationships and referential integrity, simple schema design concepts and normalization, indexing basics and their effect on performance, transactions and basic consistency concepts, and reading and interpreting simple SQL queries including SELECT JOIN GROUP BY and COUNT. This topic assesses whether a candidate understands how data is stored and related and can translate simple business questions to database queries.