SQL Data Analytics Portfolio

This repository is a curated SQL portfolio designed for Data Analyst roles.

Instead of focusing on algorithmic puzzles, the queries here reflect how SQL is actually used in analytics work — turning business questions into clear, maintainable, and explainable queries.

The problems are organized by SQL patterns commonly used in real projects, such as reporting, KPI calculation, user behavior analysis, and time-based metrics.

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🔍 What This Portfolio Demonstrates

• Translating business questions into SQL logic
• Writing readable and maintainable analytical queries
• Handling edge cases such as duplicates, NULLs, and missing records
• Adapting SQL logic across different database dialects

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🧠 Core SQL Skills

• Multi-table JOINs and subqueries
• Aggregation and KPI calculation
• Window functions (ROW_NUMBER, RANK, DENSE_RANK)
• Time-based analysis (day-over-day, monthly metrics)
• Business-oriented query design

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📂 Repository Structure (By SQL Pattern)

Each section focuses on a specific SQL pattern frequently used in analytics work.

• 01_basic_select_join
  Fundamental querying and join logic.
  Building correct joins before solving complex problems.

• 02_aggregation_groupby
  Aggregation and KPI-style queries.
  Common patterns for reporting, metrics, and summaries.

• 03_subquery_anti_join
  Anti-join and exclusion logic using EXISTS / NOT EXISTS.
  Finding missing records and handling data gaps safely.

• 04_window_functions
  Analytical queries using window functions.
  Ranking, top-N per group, and user behavior analysis.

• 05_time_series_analysis
  Time-based and trend analysis.
  Day-over-day comparison, retention-style logic, and growth metrics.

Each problem folder contains:

• explanation.md — analytical reasoning and business context
• MySQL.sql — solution in MySQL syntax
• SQLServer.sql — equivalent solution in SQL Server (T-SQL)

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📊 Selected Business-Oriented Examples

Monthly Transaction Analysis

Aggregates transaction counts and approved amounts by month and country.
Typical use cases:

• Financial reporting
• Operational dashboards
• Management summaries

Capital Gain / Loss Calculation

Computes realized profit and loss from buy/sell transaction records.
Typical use cases:

• Trading PnL reports
• Investment performance tracking

User Activity & Retention Analysis

Uses window functions to analyze user behavior over time.
Typical use cases:

• Product usage analysis
• Retention and churn metrics

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🛠 SQL Dialects

Solutions are provided in:

• MySQL
• SQL Server (T-SQL)

Queries are adapted to account for syntax differences, particularly in date handling and conditional aggregation.

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🎯 Why This Repository

This portfolio is intentionally structured to reflect real Data Analyst work:

• Queries prioritize clarity over cleverness
• Business logic is explicitly documented
• Each solution is interview-ready and explainable

Rather than showcasing how many problems were solved, the focus is on how problems are approached and communicated.

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📎 Notes

• SQL files include comments explaining analytical intent
• explanation.md documents design choices and trade-offs
• Problems are selected to mirror common analytics scenarios

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📌 This repository is actively maintained and intended for interview discussion.

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This portfolio is prepared for:

• Data Analyst
• Business Intelligence Analyst
• Analytics Engineer
• Entry / Mid-level Data Scientist (SQL-heavy roles)

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📬 About Me

• Background: Statistics / Finance / Cost Analysis
• Interested in: Data analytics, business insights, SQL optimization
• GitHub: https://github.com/KevinMeteor