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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ADF Pipeline Best Practices for Production
A pipeline that works in debug is not yet a production pipeline. This guide collects the practices that close the gap in Azure Data Factory: small pipelines within documented limits, reruns that cannot corrupt data, credentials out of the factory, deployment by release pipeline, cost control and monitoring.
BigQuery Best Practices for Analysts
An analyst can go wrong in BigQuery in three ways: a wrong number, a wasted scan, or a result nobody can reproduce. This guide gives a routine for each, with four correctness checks on 2.9 million real trips: NULL counts, filters that lose rows, days that shift with the time zone, and a join that adds rows.
Python Best Practices: Writing Pythonic Code
What "Pythonic" means in practice, as before-and-after pairs you can run: looping with enumerate and zip, unpacking, dictionary and Counter idioms, building strings, checking None and emptiness, handling files, plus naming, function design and the formatter, linter and type checker that keep code consistent.
Data Visualization Best Practices and Common Mistakes
Data visualisation best practices built around the mistakes they prevent, with the distortion measured rather than asserted: a truncated axis that exaggerates a 4% change 25 times, circles that triple a difference, percent versus percentage points, choosing the chart for the relationship, dual axes, colour and clutter.