Google Analytics··7 min read
Understanding GA4 Event Tracking
A practical mental model for designing useful GA4 events instead of collecting noise.
#GA4#Events#Measurement Strategy
Analytics · Data Science · Human Performance
Building a body of work around data, measurement, and the discipline to keep improving.
I'm Harendra Sahu. This is my professional knowledge platform for sharing practical ideas, technical work, running experiences, and lessons learned from working with data.
A simple thesis
Good analytics is not about producing more numbers. It is about making better questions easier to answer.
Use this space to build a durable record of your thinking, projects, experiments, and experience.
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The four pillars
A structure designed to connect your technical expertise with a distinctive personal point of view.
01↗
Analytics
Measurement systems, KPIs, experimentation, attribution, and analytics engineering.
02↗
Data Science
Practical statistics, Python, exploratory analysis, modelling, and data products.
03↗
Google Analytics
GA4 implementation, event design, governance, debugging, and measurement strategy.
04↗
Running
Training, races, performance, consistency, and lessons that transfer beyond sport.
Latest thinking
Articles that build the archive.
Publish practical, evidence-led writing that compounds your credibility over time.
View all articles →Analytics··8 min read
A Practical Introduction to Web Analytics
How to move from reports and dashboards toward questions, decisions, and measurable outcomes.
#Web Analytics#KPIs#Measurement
Running··5 min read
What Running Has Taught Me About Consistency
A personal reflection on repetition, patience, feedback loops, and long-term progress.
#Running#Consistency#Performance
Analytics··9 min read
From Data to Decisions: Building Better Analytics
A framework for connecting measurement to decisions that people can actually act on.
#Analytics#Decision Making#Data
Work
Selected projects
Digital Measurement Framework
FeaturedA reusable framework for connecting business questions to events, KPIs, governance, and reporting.
GA4GTMBigQuerySQL
Problem: Teams often collect large amounts of behavioral data without a clear decision model.
Approach: Map business objectives to user journeys, measurement requirements, event definitions, and decision owners.
Results: [ADD YOUR VERIFIED RESULT]
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Running Performance Analysis
FeaturedA personal data science project exploring pace, distance, consistency, and training patterns.
PythonPandasMatplotlibStatistics
Problem: Raw training logs are difficult to interpret without context and longitudinal analysis.
Approach: Clean activity data, engineer training features, visualize trends, and evaluate patterns over time.
Results: [ADD YOUR VERIFIED RESULT]
GitHub placeholder
Analytics Quality Scorecard
A practical scorecard for evaluating measurement maturity across implementation, governance, and usage.
AnalyticsSQLData Visualization
Problem: Analytics quality is often discussed qualitatively and is difficult to compare over time.
Approach: Define observable dimensions and score them consistently across teams and properties.
Results: [ADD YOUR VERIFIED RESULT]
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Running
The other laboratory.
Running provides a personal dataset of effort, recovery, consistency, uncertainty, and adaptation. Documenting that journey gives the site a human dimension that technical work alone cannot.
[YOUR RACE NAME]
[CITY, COUNTRY] · 21.1 km
[TIME]
[YOUR 10K EVENT]
[CITY, COUNTRY] · 10 km
[TIME]
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As the archive grows, use search to find articles by topic, category, or tag.