HB
Menu
AboutExperienceWorkProjects
Contact
Illustrated profile portrait of Hadi Budhy

Hadi Budhy

Analytics Engineer & Product Analyst

GitHubLinkedIn

Reliable analytics foundations for better product decisions.

I build trustworthy models and use product data to understand customer behavior, define useful metrics, and guide what teams should improve next.

View the work Get in touch

Career arc

A career built across the data lifecycle.

From reporting foundations to data systems, the focus has stayed consistent: make complex information easier to trust and act on.

01

BI foundations

Business Intelligence foundations turn operational questions into useful reporting.

02

Broader data work

Reporting expands into data pipelines, predictive models, and systems behind trustworthy analysis.

03

Decision systems

Reliable data connects with clear recommendations and better business decisions.

Selected work

Selected case studies and analysis.

6 flagship case studies show how data moves from reliable foundations to product and growth decisions.

View all projects

Analytics Engineering

Analytics engineeringanalytics engineering
event tracking
dbt
DuckDB
product analytics

Product Event Data: From Raw Clicks to Trustworthy Funnel Metrics

A small event warehouse that makes product-journey metrics reproducible, testable, and clear about what the source can actually measure.

Business questionProduct teams cannot improve a funnel when event names, user identity, and session grain are unclear. The first decision is whether the data is safe to use before anyone ranks conversion opportunities.
Decision signalThe published REES46 Electronics export supports event-level and identified-session metrics, while missing session identifiers on a small set of rows remain visible in the quality mart instead of being silently dropped.
Open case study
Analytics engineeringanalytics engineering
financial metrics
SEC data
dimensional modeling
data quality

Financial Metrics: Building a Reconciled Company Performance Mart

A filing-aware metric model that keeps reported periods, units, and restatements visible before financial trends reach a dashboard.

Business questionFinance and product leaders need a consistent view of revenue, net income, and margin, but public filing data contains multiple facts, units, periods, and restated values.
Decision signalThe model treats each reported fact as evidence with source context, then selects a documented annual view instead of assuming that the latest value is automatically comparable.
Open case study
Analytics engineeringanalytics engineering
data reliability
service operations
metric definitions
public data

Service Metrics: Separating Queue Pressure from Resolution Quality

A service-operations metric layer that keeps arrivals, backlog age, administrative closure, and resolution quality from being treated as the same outcome.

Business questionA service team sees large request queues and wants to move capacity, but complaint count alone cannot show which work is old, which queues are slow, or whether a closed request was actually resolved.
Decision signalThe model treats one NYC 311 request as the source grain, keeps open work at the analysis cutoff, and separates observed lifecycle metrics from outcomes the public source does not contain.
Open case study

Product Analytics

Product analyticscustomer growth
customer value
retention
sales analysis
python

Online Retail: Finding the Customers Behind Repeat Revenue

A transaction analysis showing where repeat revenue comes from and which markets deserve closer growth attention.

Business questionThe retailer had many transactions, but it was not clear which customers and markets created repeat revenue.
Decision signalAfter cleaning 541,909 transactions, the analysis found 4,338 identifiable customers and a strong concentration of revenue among the highest-value customers.
Open case study
Product analyticsgrowth analytics
marketplace
supply and demand
experimentation
SQL

Marketplace Supply and Demand: What Can the Public Data Tell Us?

A limited-data marketplace diagnosis that separates recorded trips from the requests and driver hours needed to measure imbalance.

Business questionA citywide incentive can be expensive when the real problem is concentrated in a few time and location windows.
Decision signalOfficial TLC data shows when recorded trips and observed driver coverage move, but it cannot directly show all ride requests or unserved customers.
Open case study

Experimentation & Growth

Experimentation & growthgrowth analytics
experimentation
causal inference
incrementality
Python

Campaign Incrementality: Did Advertising Create New Customers?

A randomized advertising analysis that separates additional conversions from customers who would have converted anyway.

Business questionA campaign can increase reported conversions while adding little incremental value if it mainly reaches people who were already likely to act.
Decision signalIn the official Criteo benchmark, the assigned advertising group converted 0.115 percentage points more often than the control group.
Open case study

Toolkit

Capabilities across professional work and public case studies.

Analytics engineering

Layered SQL models, metric definitions, event-grain thinking, data-quality checks, and reproducible pipelines.

Product analytics

Funnels, activation signals, cohorts, retention, segmentation, and product measurement plans.

Experimentation

Incrementality, holdouts, guardrails, treatment integrity, and decisions grounded in business value.

Data reliability

Source validation, freshness boundaries, reconciliation, lineage, and visible evidence limits.

Next conversation

Need metrics the product team can trust?

Get in touch to discuss event data, analytical models, product questions, and the decisions they support.

Discuss a role