Start here in Data Analytics
The most useful guides in this topic, not just the most recent.
Data Analytics Guides & Tutorials
From Excel to dashboards — roadmaps, tool comparisons, data cleaning, KPIs and business analytics for the modern data analyst.
Data Analytics articles
The Modern Data Analytics Stack Explained
The modern data analytics stack explained one layer at a time: sources, ingestion and ELT, cloud warehouses and lakehouses, transformation with dbt and its data tests, the semantic layer, BI, orchestration and governance, then one revenue number followed through every layer, and what a small team actually needs.
Outlier Detection for Analysts: Methods and Tools
Outlier detection for analysts, with four standard methods run on the same 19,773 real orders: why they flag anywhere from 53 to 1,797 orders, which suits skewed business data, how a log scale reveals suspiciously small orders, what the biggest outliers turned out to be, and when to keep, fix, cap or exclude.
Data Governance Basics Every Analyst Should Know
Data governance explained from an analyst's desk: who owns data and definitions, the six dimensions of data quality, handling personal data responsibly with reference to India's Digital Personal Data Protection Act, documenting lineage, certified datasets in BI tools, and a checklist for before you publish a report.
Self-Service Analytics: Empowering Business Teams
How to make self-service analytics work: the three ways organisations divide ownership of data and reports, why managed self-service is the usual goal, the foundations it needs, from certified data to shared metric definitions, warning signs of report sprawl, how to measure success, and how the analyst's role changes.
How to Audit a Messy Dataset Before Analysis
How to audit a dataset before analysis, with a reusable profiling function and two real examples: sessions data with missing months, inconsistent labels, duplicates and impossible values, and a scientific series whose negative numbers mean 'not available'. Plus a checklist by data quality dimension.
Forecasting in Excel: Simple Methods That Work
Forecasting in Excel with simple methods that work: the formula for each, from repeating last month to a moving average, FORECAST.LINEAR, a trend times seasonal index and FORECAST.ETS, plus an honest test on a real monthly series where the right simple method cut the error from over 40% to 12%.