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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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AWS Solutions Architect Associate: A Study Guide
A study guide for the AWS Certified Solutions Architect - Associate exam, SAA-C03, built from the official exam guide: format and passing score, the four design domains and their tasks, how scenario questions are constructed, a method for studying by trade-off, and how the exam relates to data engineering.
Securing Data on AWS: Encryption and KMS
A practical guide to securing data on AWS with encryption: what encryption at rest and in transit protect against, how AWS KMS and key policies work, envelope encryption shown step by step in code, the S3 server-side encryption options, why a KMS key adds a second permission check, and the mistakes that lock data away.
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.
Loading Data into Redshift: COPY and Best Practices
A practical guide to loading Amazon Redshift with the COPY command: why it beats INSERT, how file layout decides whether the load runs in parallel, a worked split of a real 2.96-million-row file into eight even parts with a manifest, loading Parquet, merging updates through a staging table, and verifying the load.
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.