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.
All articles
Pandas vs SQL for Data Analysis: When to Use Which
Pandas versus SQL for data analysis, compared on the same real dataset: identical answers from a GROUP BY and a groupby, a moving average as a window function and as rolling, a pivot that is one line in pandas and many in SQL, and why filtering in the database first matters when data is large.
Data Analytics Projects for Your Resume
Seven data analytics projects for a resume, each on a real, openly licensed dataset and framed as a business question: sales and returns, customer retention and value, bike-share operations, a SQL business review, country indicators, a developer survey and an Indian public dataset, with the skills each proves.
Wrangling Data Flows vs Mapping Data Flows in ADF
Azure Data Factory has two visual ways to transform data: mapping data flows, built as a graph, and wrangling with Power Query. Both run on Spark. This guide compares authoring, connectors, supported functions and limits, shows what each is good at, and explains how the choice carries into Microsoft Fabric.
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.
Excel for Data Analysis: Formulas That Matter
The Excel formulas that do most of the work in data analysis, shown as patterns on a sales table: looking up values with XLOOKUP, conditional totals with SUMIFS and COUNTIFS, cleaning text properly, handling errors without hiding problems, dynamic arrays with UNIQUE and FILTER, and readable formulas with LET.
Google Sheets for Data Analysis: Underrated Power Tools
Google Sheets features that turn it into a serious analysis tool: the QUERY function for SQL-like summaries inside a spreadsheet, ARRAYFORMULA for whole-column calculations, FILTER, REGEXEXTRACT for messy text, IMPORTRANGE for combining files, pivot tables, and where Sheets stops being the right tool.