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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Partitioning and Bucketing in Spark Explained
“Partition” means three different things in Spark: in-memory partitions, directory partitions on disk, and buckets. What each one controls, which setting or method changes it, and how to choose partition and bucket columns without creating millions of small files.
Data Engineering Interview Questions and Answers, Part 2: The Debugging Round
Some data engineering interviews skip theory and hand you a broken query: the numbers are wrong, find out why. This guide reproduces five classic pipeline bugs on real public data, shows the symptom each produces, how to diagnose it quickly and the fix an interviewer expects.
Spark vs Hadoop: What Changed and Why
What changed when Spark overtook Hadoop MapReduce: the three parts of Hadoop, the MapReduce model emulated step by step on three million taxi trips with its intermediate data written to disk, why in-memory processing and DAGs mattered, what Spark still borrows from Hadoop, and what that means today.
Data Engineer Salary in Hyderabad 2026: How the Role Pays Compared With Others
Is data engineering a well-paid role, or just a popular one? This guide answers with real 2025 survey data rather than unsourced ranges: data engineers compared with analysts, data scientists, AI/ML engineers and developers in the same country and with the same experience, and what that means for a Hyderabad offer.
Apache Iceberg vs Delta Lake vs Hudi
A comparison of the three open table formats: the problems they all solve on a data lake, Iceberg's hidden partitioning and partition evolution, Delta Lake's transaction log and Spark roots, Hudi's copy-on-write and merge-on-read tables and incremental queries, interoperability through UniForm, and a choice guide.
Cloud Data Warehouses Compared: Snowflake vs BigQuery vs Redshift
Comparisons of Snowflake, BigQuery and Redshift usually focus on architecture and pricing. For the people writing queries, the dialects matter just as much. The same six queries are translated between the three here with sqlglot, revealing function differences and one silent trap: where NULLs sort by default.