Financial Professional Insights and Regulatory KPI Analysis using SQL

Group Category: Use Case

Product Category: Database Design & Development

Sub Category: PostgreSQL

Turn regulatory data into actionable intelligence with hands-on SQL analytics for financial oversight.

Business Overview:

Financial Professional Insights and Regulatory KPI Analysis using SQL equips analysts, compliance professionals, and finance learners with the tools to explore key performance indicators across employment, certification, and disciplinary landscapes. With a PostgreSQL-compatible dataset comprising 13 interconnected tables, this product offers real-world use cases that reflect actual challenges in financial supervision and compliance. You'll write advanced SQL queries to uncover trends, identify risk factors, and create metrics-driven reports that mirror industry-grade regulatory monitoring—making it ideal for building a standout analytics portfolio or boosting career readiness.

Product Highlights:

Comprehensive PDF guide with 5 regulatory SQL use cases focused on performance and compliance metrics
Sample result images to benchmark and validate analytical output
Access to 13-table relational dataset (PostgreSQL-compatible) spanning employment, registration, exams, and disciplinary records
Includes CSV files for hands-on query practice and offline execution
Perfect for SQL learners, compliance analysts, and financial data specialists working in regulated environments

Learning Outcomes:

By completing the SQL use cases, you will:

Write complex SQL using multi-table JOINs, subqueries, filters, and grouping logic
Analyze regulatory KPIs including registration status, exam outcomes, and disciplinary trends
Use SQL date functions and aggregations for historical and pattern-based analysis
Translate real-world compliance and business requirements into executable queries

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individuals_raw

| CSV

This foundational dataset includes personal and identification details of financial professionals.

Core table for joining with other datasets like registrations, employment, and disciplinary records.
Enables analysis of naming completeness, suffixes, and profile accuracy.
Supports detailed professional identity verification and profile enrichment.

current_branch_locations_raw

| CSV

This table provides information about currently registered employers including organizational details and professional affiliations.

Facilitates employer-level analysis such as workforce size and multi-location presence.
Helps in market segmentation and identifying large or specialized firms.
Foundational for organizational structure and compliance tracking queries.

designations_raw

| CSV

This file includes details about professional designations held by individuals in the financial services industry.

Useful for analyzing competency distribution, qualification levels, and professional specialization.
Enables queries related to skills benchmarking, credential validation, and designation-based trends.
Supports compliance with certification standards and continuing education requirements.

exams_raw

| CSV

Contains core personal and professional identifiers for individuals in the regulatory dataset.

Serves as a foundational table to join with other datasets for comprehensive professional profiles.
Allows for completeness checks, suffix analysis, and identity mapping.
Essential for data quality checks, record linkage, and profile enrichment.

other_names_raw

| CSV

This dataset documents alternative names or aliases used by financial professionals.

Supports thorough identity verification and helps prevent duplicate or fraudulent entries.
Critical for compliance teams during due diligence, background checks, and regulatory filings.
Enables enriched profiling by linking aliases to main identities.

current_employers_raw

| CSV

This dataset provides structured information on current employers of financial professionals, including organization names and affiliations.

Enables organizational mapping, geographic coverage analysis, and branch-level insights.
Supports analysis of industry structure, concentration, and workforce scale.
Useful for identifying firms with large-scale operations or complex multi-location setups.

Financial Professional Insights and Regulatory KPI Analysis using SQL

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