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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Building a Streaming Pipeline with Kafka and Spark
A streaming pipeline built and run end to end: 77,033 real taxi events on a Kafka topic, read by Spark Structured Streaming, parsed from JSON, aggregated into hourly event-time windows with a watermark and written to a sink, with the real output showing why the final window is not emitted, plus what production adds.
Building Your First Interactive Dashboard
A first interactive dashboard, built step by step on real sales data: preparing one tidy table, adding filters that recalculate every KPI, showing the trend, and then testing the interactions automatically, the step most beginners skip, with notes on doing the same in Power BI, Tableau or Looker Studio.
Building a Data Warehouse: A Step-by-Step Guide
A hands-on guide to building a data warehouse: choosing the business process and grain, staging raw data, building date, zone and payment dimensions, loading a trip fact table with rules, testing for orphan keys, and querying the star, all run in DuckDB on real New York taxi data, plus what production adds.
Building a Data Lake on AWS with S3 and Glue
A step-by-step guide to building a data lake on AWS: how to lay out an S3 bucket in zones, land raw data unchanged, write a cleaned Parquet layer, and register tables in the Glue Data Catalog, shown end to end on a real 2.96-million-row file, followed by querying, security, cost controls and how lakes become swamps.
Building a Prediction API: A Complete Walkthrough
A prediction API can return confident, well-formed and completely wrong answers. This walkthrough builds a FastAPI service for a real model and the four tests that catch what usual API tests miss: a feature-order bug, inputs that should be refused, a NaN that crashes the error handler, and batch results that drift.
Building a 30-60-90 Day Plan for a New Data Job
Research on onboarding suggests new employees have about 90 days to prove themselves, and that clarity about the role, confidence and relationships drive success. This guide turns that into a 30-60-90 day plan for data analysts, scientists and engineers, with goals for each phase and an example you can adapt.