Hubble Database

Financial Big Data Platform

Business Database RPA System

Hubble Database is a financial big data platform that transforms the Korean corporate ecosystem through original DB RPA (Robotic Process Automation) technology.

By unifying fragmented information into a single database, it reduces preprocessing time and enables accurate, timely analysis for corporate and financial research.
COMPANIES IDENTIFIED
130
M+
INFORMATION TYPE
10
+
ALTERNATIVE DATA POINTS
300
+
Platform (KR)

Step 01. Identification

1192010
 Companies Identified
Leveraging the big data technology of the Hubble Database, we have successfully identified all domestic corporations and digitized the corporate ecosystem of South Korea.
Based on 
May, 2025
 (Excluding closed business)
Identified Entities
1192010
Corporate Entities
1505881
Data Coverage
83
%

Step 02. Data Collection

More than 300 Alternative Data Points in 10 Information Type
Alternative data refers to non-financial information such as organizational structure, certifications, websites, intellectual property, and media coverage that enables more precise and timely analysis of companies and their business performance beyond traditional financial metrics and disclosures.

By utilizing diverse alternative data, including organizational structure, certifications, and media coverage, we offer a comprehensive company analysis, enhancing investment opportunities and proactive risk management.
Summary
Service information, Business code
Web
URL, Domain verification, Response speed
Organization
Monthly hires, Resignation, Salary, Organization size
Technology
IP (Intellectual property), R&D, Design
Certification
Certification, issued by government and private institutions
Industry
Technology type, Industry classification
Geolocation
Address change record, Land price, Proximity
Funding
Investment level, Amount, Key investor
Awards
Government citations, Major events / project
Media
News Press, SNS, Digital contents

Step 03. Processing

Our big data capabilities operate automated standardization and preprocessing processes on the collected raw data, storing it in the database in an optimal format for advanced analysis and AI training.
Validity Check
Data validation and consistency verificaiton according to internal regulations
Standard Formatting
Data transformation to align with common formats and standards
Data Integration
Integration of data from various sources within the same company