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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Amazon Redshift Explained: The Cloud Data Warehouse
An introduction to Amazon Redshift, AWS's data warehouse: how a leader node, compute nodes and slices run a query in parallel, why data is stored in columns, how managed storage separates compute from storage, Serverless versus a provisioned cluster, how it differs from PostgreSQL, and what to learn first.
Data Modeling in Power BI: Star Schema Explained
Star schema modelling for Power BI: what fact and dimension tables are, why visuals query them efficiently, and a real 541,909-row flat export turned into a star, exposing the problems that break relationships, from non-unique keys to missing members, plus date tables, explicit measures and related design patterns.
Data Analyst Salary in Hyderabad 2026: What Moves an Analyst's Pay
Analyst pay varies more than most people expect, and two things the analyst controls stand out in real 2025 survey data: whether they code, and which industry they work in. This guide shows both, compared fairly with same-experience peers, and explains what it means for analysts in Hyderabad.
How to Plan a 5-Year Career in Data
Five-year career plans fail when they predict job titles; they work when they set direction and review it often. Employer forecasts put big data roles among the fastest-growing jobs, and survey data shows what data professionals want to learn next. This guide uses both to build a five-year plan with yearly milestones.
AWS Glue Data Catalog and Crawlers Explained
The Glue Data Catalog is the index of an AWS data lake, and crawlers are the usual way to fill it. This guide explains what the catalog stores, how a crawler classifies files and decides between tables and partitions, what three real files with drifting schemas show, and the settings that keep crawlers predictable.
Amazon EMR Explained: Big Data on AWS
Amazon EMR runs Spark, Hadoop, Hive and other big data frameworks on AWS. This guide explains primary, core and task nodes, why data belongs in S3 and not in the cluster's HDFS, how work is submitted as steps, transient versus long-running clusters, the Serverless and EKS options, and what decides the bill.