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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ETL vs ELT: Differences and When to Use Each
The difference between ETL and ELT, shown by running both on three million real taxi trips: ETL stores 31 transformed rows while ELT keeps every raw row and transforms in SQL, then a business rule changes and only ELT can re-derive without re-extracting; plus when to choose each, reverse ETL and streaming.
Power BI vs Excel: When to Use Each Tool
A task-by-task guide to choosing between Power BI and Excel at work: the signs a workbook has outgrown Excel, what Excel still does better, the worksheet row limit tested on a real two-sheet retail dataset, and the ways the two tools work together, from Power Query to Analyze in Excel and connected tables.
Power BI Custom Visuals: When and How to Use Them
Using custom visuals in Power BI: the three places visuals come from, what Microsoft's certification does and does not check, the data, licensing and update risks of third-party code, features a non-certified visual loses, how organisations approve visuals centrally, and a checklist before adding one to a report.
Athena vs Redshift: When to Use Each
Athena and Redshift both run SQL on AWS, but one is a query service over files in S3 and the other is a data warehouse. This comparison covers where the data lives, how each is billed, behaviour under many users, updates and modelling, AWS's own guidance, and the common design that uses both.
PySpark vs Pandas: When to Use Which
When to use PySpark and when to use pandas: the same hourly revenue query written in both and checked to give identical answers on three million taxi trips, the eightfold memory cost of loading the data into pandas, eager versus lazy execution, Arrow and toPandas, pandas API on Spark, and a decision guide.
Career Growth: When to Stay vs When to Switch
Switching jobs usually pays more, but not always: in 29 years of US wage data, the switcher premium vanished after the financial crisis and peaked in 2022. Combined with what 1,245 data professionals say makes a job satisfying, it gives a practical way to decide whether to stay or switch.