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Interview Questions Guides & Tutorials
Curated interview question banks with answers — SQL, Python, data science, Spark, Power BI, AWS, ADF and more.
Interview Questions articles
DAX Interview Questions for Power BI Developers
DAX interviews test whether you understand evaluation context, not whether you remember function names. Six classic questions are answered with real DAX measures, evaluated by the same kind of engine that powers Power BI, on a month of real online orders, where the wrong formula overstates revenue 45,000 times.
Docker and Kubernetes Interview Questions for ML
Container questions in ML interviews are about the mistakes that make images slow to build, huge, insecure or killed in production. Four are answered with real Docker builds and runs, from a cache that survives a code change to a container killed with exit code 137, then the Kubernetes questions that follow.
Excel Interview Questions for Data Analysts
Excel interviews rarely ask what a function does; they ask why a formula gave the wrong answer. Seven questions are answered with formulas calculated by Microsoft Excel itself on New York's taxi zone table: an approximate VLOOKUP that was wrong 18 times in 20, an ID stored as text, and a date that depends on settings.
GCP Interview Questions for Data Engineers
Google Cloud data engineering interviews go deepest on streaming: event time, watermarks and late data in Dataflow. This guide runs real Apache Beam pipelines on a busy hour of New York taxi pickups to show windows and what happens to a late event, then covers Pub/Sub delivery, storage classes and IAM.
Hadoop Interview Questions and Answers
Hadoop still comes up in data engineering interviews, usually as questions about how HDFS and MapReduce work underneath. Four are answered by running a real Hadoop 3.4.1 node on two million household power readings: block counts, an under-replicated file, 31 small files and a MapReduce job with its counters.
PySpark Interview Questions with Examples
PySpark interview questions test the API details that decide whether a job is correct and fast. Seven are answered on a real two-million-row electricity file that fights back: a placeholder that turns numbers into strings, dates without leading zeros that Spark 3 will not parse, and a UDF that drags rows into Python.