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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From Excel to SQL: A Smooth Transition Guide
A transition guide from Excel to SQL that starts from what you already know: filters become WHERE, SUMIFS becomes GROUP BY, XLOOKUP becomes a join, COUNTIFS and IF become CASE, and pivot tables become conditional aggregation, each shown as a real query with its output, plus the mindset shifts and pitfalls to expect.
Cloud SQL vs Spanner vs Bigtable: When to Use Each
Cloud SQL is a managed MySQL, PostgreSQL or SQL Server. Spanner is a relational database that scales across regions with strong consistency. Bigtable is a wide-column store for huge volumes read by key. This guide compares them, models on real data why a Bigtable row key decides everything, and gives a way to choose.
BigQuery ML: Machine Learning with SQL
BigQuery ML trains and runs machine learning models with SQL, on data that never leaves the warehouse. This guide covers the statements, model types and pricing, then reproduces a logistic regression locally on 300,000 real trips to show what the evaluation numbers mean and three ways an easy model can mislead.
Window Functions in SQL for Data Engineers
The window function patterns data engineers use every week, each run on the real Chinook database: ROW_NUMBER for the latest row per key, RANK and DENSE_RANK on ties, LAG for gaps between events, frames for running totals and moving averages, and the default RANGE frame that silently changes a running total.
Copying Data from On-Prem SQL to Azure with ADF
Azure Data Factory cannot reach a database behind your firewall, so a self-hosted integration runtime inside the network does the work. This guide covers how that flow operates, what the machine and firewall need, the linked service and Copy activity definitions, credentials, large tables and the usual failures.
Amazon Athena: Querying S3 with SQL
An explanation of Amazon Athena for people new to it: what the service is, how a table is only metadata pointing at files in S3, what happens when a query runs, where results go, how billing by bytes scanned works, how workgroups cap spending, and where Athena fits beside Redshift and EMR.