Core

Change Data Capture

Change Data Capture (CDC) streams the inserts, updates, and deletes from a source database so downstream systems stay in sync without expensive full reloads. It powers incremental pipelines, real-time analytics, and keeping a search index or feature store fresh. The key concerns are handling updates and deletes (not just inserts), ordering, and idempotent application of the change stream. Applied-AI interviews probe it because keeping a RAG index, feature store, or warehouse current is a constant need, and full reloads do not scale.

a free account unlocks the core curriculum tier · no card

COURSES COVERING THIS TOPIC

No lesson covers this one directly yet. These teach the surrounding topic from the beginning.

Applied AI Engineering·The interviewPremium12mTurning this course into a study planA concrete four-week plan mapping the seven modules onto the question bank, plus what to do differently if your interview is next week rather than next month.

RELATED CONCEPTS

Idempotent Data Pipelines: Reruns Without Duplicate Rows Data Quality and Contracts The RAG Pipeline Feature Store: Online vs Offline and Training-Serving Skew

PRACTICE THIS IN REAL QUESTIONS

SQL & Data EngineeringHow do you keep an analytics warehouse in sync with a source database using change data capture?→SQL & Data EngineeringCompare CDC variants: log-based, query-based, and trigger-based. What are the failure modes of each?→SQL & Data EngineeringSCD Type 2 in Delta Lake: track history with one atomic MERGE.→SQL & Data EngineeringGroup a stream of user events into sessions in SQL (30-minute inactivity gap) using window functions.→SQL & Data EngineeringTop-N per group in SQL: ROW_NUMBER vs RANK vs DENSE_RANK.→SQL & Data EngineeringDeduplicate events exactly-once over a sliding 7-day window in a high-throughput stream without running out of memory.→

COMPANIES THAT ASSUME THIS

Scale AI Palantir Databricks Snowflake Zendesk Clay

NEXT IN DATA & SQL ENGINEERINGDeduplication (Exact and Fuzzy)→