Basic Professional Data Analysis
Group Category: Use Case
|Product Category: Database Design & Development
|Sub Category: PostgreSQL
About this Product
Get started with real-world SQL by analyzing professional data quality, completeness, and structure.
Business Overview:
Basic Professional Data Analysis is the perfect entry point for those beginning their journey in SQL and data analysis. Designed for learners, interns, and junior analysts, this SQL-based project walks you through foundational tasks such as counting records, checking data completeness, validating IDs, and assessing data quality. Using a PostgreSQL-compatible dataset of 13 relational tables, you’ll perform simple yet meaningful queries that help build core skills in regulatory data contexts. It’s a practical way to learn SQL while analyzing actual business scenarios in the financial services sector.
Product Highlights:
- A beginner-friendly PDF guide featuring 5 SQL-based foundational use cases
- Hands-on SQL practice for data completeness, validation, and source tracking
- Based on PostgreSQL datasets with real-world schema structure
- Great for early learners, data interns, or junior analysts building confidence
- Useful for portfolios, bootcamp practice, or basic audit prep
Learning Outcome:
By completing these use cases, you’ll gain skills in:
- Writing basic SQL queries with
SELECT,GROUP BY, andCOUNT - Validating primary key uniqueness and detecting duplicates
- Checking for null or missing data in key fields
- Understanding source file distribution and data origin tracking
Resources
This dataset contains raw profile data of financial professionals, serving as a foundational input for SQL-based analysis.
- Includes key fields like first name, last name, middle name, suffix, registration status, professional ID, and data source.
- Enables use cases such as name completeness checks, active registration tracking, ID validation, and source file analysis.
- Supports data quality assessment, regulatory reporting, and compliance analytics.
- Ideal for use in beginner to intermediate SQL tasks focused on data structure, filtering, and aggregation.
- Acts as the core reference table for linking to other datasets in broader financial compliance projects.
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