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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GCP vs AWS vs Azure for Data Engineering
The three large clouds solve the data engineering problem with the same building blocks under different names. This comparison maps the services layer by layer using the vendors' own tables, shows where those tables disagree, writes one file load for BigQuery, Redshift and Synapse, and gives plain rules for choosing.
Securing Data on GCP: Encryption and DLP
Google Cloud encrypts stored data by default, so that is rarely the gap. The work is knowing where sensitive data is and limiting who sees it in clear. This guide covers default encryption, customer-managed keys, Sensitive Data Protection and BigQuery masking, and shows why hashing a phone number protects little.
Nested and Repeated Fields in BigQuery
BigQuery can keep an order's line items inside the order's own row, as an array of structs. This guide explains nested and repeated fields, builds one from a real sample database, shows how they stop a join inflating totals nearly ninefold, and covers UNNEST, array subqueries, limits and when a join is better.
GCP Data Engineer Salary in India 2026: Remote Work, Google Cloud and Pay
Do remote jobs pay more in India, and does Google Cloud experience raise pay? Real 2025 survey data gives a careful answer. Remote and hybrid workers earned more than in-person workers, but mostly because of who employs them, and Google Cloud users were paid close to their peers. Here is the evidence.
Streaming Data into BigQuery: A Practical Guide
Streaming new events into BigQuery is well covered. Streaming changes, where rows are updated and deleted, needs BigQuery's change data capture. This practical guide covers the pseudocolumns, primary keys, sequence numbers and max_staleness, and simulates the ordering rules to show how out-of-order changes go wrong.
BigQuery Best Practices for Analysts
An analyst can go wrong in BigQuery in three ways: a wrong number, a wasted scan, or a result nobody can reproduce. This guide gives a routine for each, with four correctness checks on 2.9 million real trips: NULL counts, filters that lose rows, days that shift with the time zone, and a join that adds rows.