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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Azure Data Engineering Projects for Your Portfolio
Five Azure data engineering projects for a portfolio, each on real public data and each built to demonstrate one skill an interviewer will ask about: metadata-driven ingestion, incremental loading, Spark cleaning with quality rules, a dimensional model with history, and event-driven processing with alerts.
Data Analytics Roadmap for Non-Tech Backgrounds
A data analytics roadmap for people coming from non-technical fields such as sales, HR, commerce, operations or the arts: what you already have that helps, the maths you really need, a learning order that starts inside your current job, how to handle jargon and doubt, and how to present your background as an advantage.
AWS Certified Data Engineer Associate: Exam Guide
A guide to the AWS Certified Data Engineer - Associate exam, DEA-C01, taken from the official exam guide: format, length, cost and passing score, the four content domains and their weightings, what is out of scope, the services to know, and a study plan organised by domain with hands-on practice for each.
AWS CloudWatch for Monitoring Data Pipelines
Monitoring a data pipeline means knowing when it failed, when it did not run, and when it ran but produced bad data. This guide shows how Amazon CloudWatch covers all three: the metrics worth publishing, alarm settings including missing data, logs, EventBridge events from Glue, and a worked example in boto3.
Migrating Data to AWS: DMS and Best Practices
AWS Database Migration Service copies databases into AWS and keeps them in step with ongoing changes. This guide explains its components, the three task types, what DMS writes to S3 for a data lake, how to turn its change records into a current table on real data, and the documented practices for load and validation.
AWS Data Engineering Projects for Your Portfolio
Five AWS data engineering projects for a portfolio, on real public data: a serverless lake queried with Athena, event-driven ingestion with Lambda, an orchestrated Glue pipeline, a streaming path through Kinesis and Firehose, and a Redshift warehouse. Each lists the services, what it proves and cost cautions.