Intermediate~3h
Streaming Fundamentals in Data Engineering CoreInterview Readiness Check
Batch vs streaming, event time vs processing time, windowing (tumbling, sliding, session), watermarks for handling late data, exactly-once vs at-least-once semantics, the lambda and kappa architectures..
streamingevent timeprocessing timewindowingwatermarkexactly-oncelambda architecturekappa architecturelate data
Learning path
Batch ETL & Pipeline Design→Streaming Fundamentals ← you are here→Kafka & Streaming SystemsSpark Structured Streaming
Try a sample question
What is the key difference between event time and processing time in streaming systems?
A.Event time is when the event actually occurred (in the source); processing time is when the streaming system received and processed it
B.Event time is the wall clock time on the server; processing time is the time in UTC
C.Event time is used for batch; processing time is used for streaming
D.They are the same thing expressed in different time zones
Sign up free to take the full check and see the answer with an explanation.
What this module tests
- Conceptual understanding of streaming fundamentals fundamentals
- Trade-offs and design decisions in real system scenarios
- streaming and event time — applied knowledge
- Interview-style reasoning and explanation quality
Free to start
Take the Streaming Fundamentals check →
10 questions · Dimension scoring · AI coach feedback · Shareable result
Test your knowledge — free →No credit card · Takes 10–15 min
Frequently asked questions
- What does the Streaming Fundamentals check test?
- The check covers batch vs streaming, event time vs processing time, windowing (tumbling, sliding, session), watermarks for handling late data, exactly-once vs at-least-once semantics, the lambda and kappa architectures.. Questions span beginner to advanced difficulty and test both conceptual understanding and practical trade-off reasoning.
- What keywords should I know for Streaming Fundamentals?
- Key concepts include: streaming, event time, processing time, windowing, watermark, exactly-once, lambda architecture, kappa architecture, late data. These frequently appear in data engineering core interviews at product and infrastructure companies.
- How many questions are in the check?
- Each check has 10 questions — a mix of MCQ and short-answer. You get scored by dimension (e.g., scalability, consistency) so you know exactly where to focus.
- How long does it take to study Streaming Fundamentals?
- Most engineers spend around 3 hours on this module. The check itself takes about 10–15 minutes. You can retake it up to 3 times per day.
- What prerequisite knowledge do I need before Streaming Fundamentals?
- Streaming Fundamentals builds on Batch ETL & Pipeline Design. Complete those first for the best results.
- Is streaming, event time, processing time covered?
- Yes. The Streaming Fundamentals module covers streaming, event time, processing time among other key concepts. The check includes questions that reflect real data engineering core interview patterns.