IT Career Guides & Free Resources
Expert roadmaps, tutorials, salary guides and interview prep across Data Science, Generative AI, Python, Cloud & Analytics — written by GloryTecks trainers in Hyderabad.
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SQL Interview Questions: Top 50 with Answers
Fifty SQL interview questions with answers checked on PostgreSQL, DuckDB and SQLite against one small practice schema: evaluation order, NULL logic, joins and fan-out, window functions, dates, and performance, including where the three engines disagree.
Python Interview Questions: Top 50 with Answers
Fifty conceptual Python interview questions with short, precise answers, grouped by topic: basics, types and mutability, data structures, functions and scope, OOP, iterators and decorators, errors and files, and internals, with runnable examples for the ones people most often get wrong.
Power BI Interview Questions: Top 40 with Answers
Forty Power BI interview questions with concise answers checked against Microsoft's documentation, from fundamentals and Power Query through star schema modelling, DAX and filter context, report features, the Power BI service, security and performance, to scenario questions that test judgement, and how to answer well.
BigQuery Interview Questions and Answers
BigQuery interviews mix SQL with cost: what a query will be billed, and how table design changes it. Seven questions are answered with GoogleSQL run locally on real New York taxi data and with Google's own documentation: column costs, LIMIT, approximate counts, QUALIFY, arrays, and partitioning with clustering.
Databricks Interview Questions and Answers
Most Databricks interview questions are really Delta Lake questions. Six are answered by building a real Delta table from daily bike-share data: what each write adds to the transaction log, time travel, a MERGE that rejects duplicate keys, schema enforcement, compacting 32 small files into one, and VACUUM.
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.