Professional Profile Analysis

Group Category: Use Case

Product Category: Database Design & Development

Sub Category: PostgreSQL

Explore workforce trends, certifications, and compliance status through real-world SQL analytics.

Business Overview:

Demographic & Career Analysis of Financial Professionals gives you the tools to investigate how licensed individuals in the financial industry move, grow, and comply. This hands-on SQL product is perfect for analysts, learners, and compliance professionals who want to dissect career paths, certification trends, and geographic patterns using structured PostgreSQL data. The scenarios simulate real regulatory and operational queries—like tracking professional history, identifying compliance gaps, or mapping the concentration of credentials—making this ideal for building project portfolios or sharpening compliance reporting skills.

Product Highlights:

  • A structured PDF guide featuring 5 in-depth SQL use cases
  • Sample output screenshots for benchmarking your solutions
  • PostgreSQL-compatible dataset with relational tables (individuals, certifications, employment, locations, etc.)
  • Includes scenarios on certification status, career progression, and disciplinary actions
  • Practical for learners, analysts, HR tech professionals, and compliance teams working with regulatory data

Learning Outcomes:

By completing these use cases, you will:

  • Master multi-table JOINs, conditional logic, and aggregate functions in SQL
  • Handle incomplete or missing data using robust SQL techniques
  • Extract and analyze trends in certifications, professional demographics, and geographic mobility
  • Build complete professional snapshots using data from multiple sources
  • Develop SQL skills directly applicable to compliance analytics, workforce planning, and financial services regulation
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current_employers_raw
current_employers_raw
| CSV

Description:
This dataset contains information about the current employment affiliations of financial professionals. It includes organization names, locations, and employment statuses—supporting market coverage, organizational analysis, and geographic distribution studies.

  • Details current employer names and branch locations
  • Supports analysis of firm-level footprint and branch density
  • Structured to link with individuals for profiling and affiliation analysis
  • Enables identification of multi-location organizations and employment clusters
  • Ideal for spatial and organizational SQL queries
disciplinary_records_raw
disciplinary_records_raw
| CSV

This CSV dataset contains raw disciplinary records of financial professionals, serving as a key input for compliance and risk analysis use cases. It includes information on violations, action types, enforcement dates, and resolution status. The data is structured for PostgreSQL-based querying and supports use cases involving risk profiling, compliance monitoring, and regulatory reporting.

  • Raw dataset capturing disciplinary actions across financial professionals
  • Includes fields for action types, dates, descriptions, and resolution status
  • Enables SQL-based analysis of compliance flags and enforcement patterns
  • Designed to work alongside individual and employment datasets for relational querying
  • Ideal for building use cases in regulatory compliance, risk heatmaps, and audit readiness
other_names_raw
other_names_raw
| CSV

Description:
This dataset contains historical name variations used by financial professionals. It is crucial for identity resolution, audit trails, and background verification across different timeframes or regulatory filings.

  • Tracks previous names or aliases linked to professional IDs
  • Aids in resolving discrepancies during compliance checks
  • Supports audit history and verification processes
  • Useful for tracking career progression under name changes
  • Enables robust linkage of multi-year or multi-role records
designations_raw
designations_raw
| CSV

Description:
This CSV contains data on the professional designations and certifications held by financial professionals. It supports skills distribution analysis, designation trend tracking, and HR insights into workforce specialization.

  • Includes designation names, issue dates, and professional references
  • Enables SQL queries on skillsets, specialization, and certification frequency
  • Useful for workforce capability mapping and HR planning
  • Complements risk profiling and role-specific credential analysis
  • Supports professional recognition and benchmarking use cases
individuals_raw
individuals_raw
| CSV

Description:
This CSV dataset contains raw individual-level records used for analyzing financial professionals within the regulatory and compliance domain. It includes key attributes such as personal identifiers, employment history, registration details, designations, and geographic metadata. The dataset supports advanced SQL querying for compliance reporting, professional profiling, and demographic insights.

  • Core dataset supporting multiple advanced SQL use cases
  • Structured for PostgreSQL with relational keys and standardized field types
  • Enables analysis of professional profiles, employment trends, and regulatory flags
  • Ideal for hands-on practice in filtering, joining, aggregating, and risk scoring
  • Complements PDF-based instructional guides for end-to-end analytics workflow
other_businesses_raw
other_businesses_raw
| CSV

Description:
This dataset captures information about additional business interests declared by financial professionals. It's vital for conflict-of-interest checks and understanding professional obligations outside primary employment.

  • Lists declared outside business activities and related metadata
  • Essential for conflict-of-interest monitoring and policy enforcement
  • Supports regulatory compliance and disclosure verification use cases
  • Structured for joining with individual profiles
  • Enhances risk analysis related to business affiliations
Professional Profile Analysis

$2.00 $1.25 37% OFF

Topics: SQL

Languages: English

Skills: Advanced SQL, Regulatory Analytics, Data Auditing, Financial Risk Analysis, Compliance Automation

Business Domain: Finance and Regulatory Compliance

Level: Advanced

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