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.
All articles
Looker and Looker Studio on GCP Explained
Google has two BI tools with similar names and different jobs. Data Studio, the new name for Looker Studio, builds self-service reports at no cost. Looker adds a central model that defines each metric once. This guide compares them and uses a real database to show the mistake a shared model prevents.
GCP Networking Basics for Data Engineers
Most data services on Google Cloud need no network setup, until a job must run on private addresses or reach a database. This guide covers VPC networks, subnets, firewall rules, Private Google Access, Cloud NAT and service perimeters, and sizes subnets for pipeline workers with a short script.
BigQuery SQL: Tips, Tricks and Optimization
BigQuery rewards a few specific habits. This guide gives twelve, each tied to Google's own guidance: read fewer columns, filter and aggregate before joining, do several measures in one pass with COUNTIF, guard division with SAFE_DIVIDE, and stop expecting CTEs to be cached. Three are shown on 2.9 million real trips.
Cloud Composer (Airflow) on GCP Explained
Cloud Composer is Google Cloud's managed Apache Airflow, now being renamed Managed Service for Apache Airflow. This guide explains what an environment contains, how the three generations differ, shows a DAG built from Google operators, works out what an always-on environment costs and when a simpler scheduler will do.
Migrating to BigQuery: A Practical Playbook
Moving a warehouse to BigQuery is less a copy job than a proof: that the SQL still means the same thing and the numbers still match. This playbook follows Google's iterative method, then reproduces two steps locally: a translator that gets one statement wrong, and a copy that passes row counts while 23 rows differ.
Scheduling Queries in BigQuery
A scheduled query is SQL that BigQuery runs for you on a timetable. This guide covers the run parameters, destination table templates checked against Google's own examples, backfills, credentials and notifications, and shows on real data why an appending statement doubles on a rerun while a MERGE does not.