Help your
“DATA”
make sense.
I transform complex, messy datasets into clear insights, high-impact visualizations, and smarter business decisions.
DATA IS ONLY
USEFUL WHEN IT
TELLS A STORY.
I'm Siam Azad, a Data Analyst obsessed with translating messy, unstructured data into clear, actionable business strategies.
Real-world data rarely arrives in clean rows and perfect schemas. It arrives with missing keys, currency inconsistencies, duplicate webhooks, and noisy anomalies.
My craft begins by stripping away the noise, establishing statistical integrity, and transforming chaotic transactional data into clear business intelligence.
Live interactive transformation simulator
| ID | ORDER_DATE | REGION | PRODUCT | AMOUNT | STATUS |
|---|---|---|---|---|---|
| TRX-8901 | 2025-01-02 | north_am | SKU_402 | $12,450.00 | COMPLETED |
| TRX-8902 | 2025/01/03 | NULL | sku-402 | 18700 | pending |
| TRX-8903 | 04-Jan-2025 | EMEA | N/A | NULL | REFUNDED |
| TRX-8904 | 2025-01-05 | APAC | SKU-990 | -$15,200.00 | DISPUTED |
| TRX-8904_DUP | 2025-01-05 | APAC | SKU-990 | -$15,200.00 | DISPUTED |
| TRX-8905 | 2025-01-06 | north_am | SKU-402 | 21950.5 | COMPLETED |
MY TOOLKIT FOR
FINDING CLARITY.
I don't rely on superficial percentage bars. Here is the operational code, architecture, and querying frameworks I use daily to solve business problems.
WITH cohort_analysis AS (
SELECT
user_id,
DATE_TRUNC('month', created_at) AS signup_cohort,
FIRST_VALUE(revenue) OVER(
PARTITION BY user_id
ORDER BY created_at
) AS initial_order_val
FROM raw_transactions
)
SELECT
signup_cohort,
COUNT(DISTINCT user_id) AS active_users,
ROUND(AVG(initial_order_val), 2) AS avg_initial_aov
FROM cohort_analysis
GROUP BY 1
ORDER BY 1 DESC;SELECTED
ANALYSES.
In-depth exploratory, predictive, and business intelligence case studies. Each project highlights real business context, technical pipelines, and measurable outcomes.
E-Commerce Revenue & Retention Analysis
A deep dive exploratory analysis of 450,000+ transactional records to identify regional sales drops, product mix cannibalization, and cohort retention decay.
Customer Churn & Risk Segmentation
Predictive behavioral segmentation isolating key churn drivers across usage frequency, support ticket volume, and payment friction.
Executive Business Performance Suite
A consolidated financial and operational dashboard delivering real-time visibility into blended CAC, LTV/CAC ratios, and departmental burn rates.
Market & Product Affinity Insights
Applied Apriori association algorithms and price elasticity modeling across 850 SKUs to optimize bundle pricing and merchandising placement.
NUMBERS,
MADE VISIBLE.
Interactive chart modules demonstrating multivariate statistical plotting, time-series forecasting, and behavioral risk scoring.
Historical Baseline vs. Cohort Intervention Model
FROM CHAOS
TO CLARITY.
The core philosophy: every dataset undergoes a 5-step metamorphosis from unorganized noise into decisive business intelligence.
Unstructured & Noisy
Thousands of scattered transactional events, unstandardized formats, missing fields, and noisy telemetry.
LET'S FIND
THE NEXT
INSIGHT.
Have a complex dataset that needs clarity? Or looking for a Data Analyst to join your analytics, product, or BI team? Let's build something impactful together.
System ready for new telemetry, queries, and business challenges.
Send a direct analytical brief or role inquiry