eng-datasolution

SDQ

(Smart Data Quality)

SDQ with systematic enterprise data quality managing process, dedicate on improving the efficiency of enterprise level work with improved data quality and secure of stability
[Smart] Provides DA(Data Architecture) work through standard data(word, term, domain) managing.
[Data] With easy-structure, approachable with anyone, it deals data quality managing process fast and stable.
[Quality] Checking and result analyzing of the quality-checking object when it comes to data quality checking and improving.

Benefits of solution

Data quality managing efficiency improving
By increasing the visibility of data test result, it’s easy to check quality situation. Also, with simple but smart data quality test and report, improve the efficiency of data quality managing work
Increased credibility of Data quality
By creating the schedule, it proceeds regular automated-checking. Continuous quality state checking and improving and securing the credibility of data is possible.
Securing the safety of Data managing
Error estimate data is provided for searching fundamental reason for problem and based on the process, program chase the source program that occurs the problem, which leads to data safety securing of operation system.

Characteristic of SDQ	Specifics
Providing the quality specifications after Ministry of Public Administration and Security	Provides the quality specifications of Ministry of Public Administration and Security Use standard, structural diagnosis along with value diagnosis Specialized quality-managing standard including possibility of choosing open data
Simple but Smart quality test	Simple design focused on data quality testing Convenient functions of data quality checking based on domain User-oriented function with instant UI structure
Fast and Convenient quality checking	Securing quality test using multi-thread function Efficient resource using with reservation function Possible parallel processing function of DBMS
OPEN SOURCE S/W based solution	Architecture considering expendability and flexibility Supports various platforms

SDQ for AI

(AI training data quality Management solution)

SDQ with systematic enterprise data quality managing process, dedicate on improving the efficiency of enterprise level work with improved data quality and secure of stability

Benefits of solution

Comprehensive Quality Management Across Diverse AI Domains
SDQ for AI delivers advanced inspection and analytical capabilities for AI training data across domains such as natural language processing, healthcare, and autonomous driving.Backed by B2EN’s experience in the Korean government’s “AI Training Data Syntactic Accuracy Inspection Service” project, it offers proven, national-level expertise in AI data quality management across industries.
Enhanced Usability with GUI-Based Configuration
With its GUI-based configuration, SDQ for AI allows non-developers to easily conduct quality inspections. Complex hierarchical datasets are presented in intuitive grid formats, improving communication between designers and quality managers.
High-Speed Inspection for Large-Scale Training Data
SDQ for AI guarantees high-speed inspection and analytical performance, even for large-scale AI training datasets consisting of over 5 million files.

Characteristic of SDQ for AI	Specifics
Automated Validation Rule Generation	Automatically generates validation rules based on global-standard JSON schemas. Converts complex hierarchical data structures into intuitive tabular views for clear and efficient data structure analysis. Provides GUI-based editing capabilities for detailed customization of validation rules.
Syntactic Accuracy Validation	Provides validation functions aligned with the three detailed syntactic accuracy indicators defined in the NIA Quality Management Guidelines. Supports file completeness validation. Performs syntactic accuracy validation for annotation files in various formats, including XML and CSV.
Statistical Diversity Analysis	Offers statistical diversity analysis through a GUI, including dataset size and class distribution. Enables advanced statistical calculations by combining and transforming multiple data attributes to generate customized insights.
Automated Comprehensive Reporting	Automatically generates comprehensive reports for syntactic accuracy validation and statistical diversity analysis in Excel format. Provides detailed error lists by validation indicator in CSV format.

SMETA

(Smart Metadata)

Combined with B2EN various public data-opening experiences and technical capabilities, SMETA is a solution that unifies and manages metadata across the company. SMETA provides information about data standards, data structures, and the impact of data changes, ensures consistency of data owned by organizations, and provides incredible transparency to data assets, including quality infrastructure and improved data accessibility.

Benefits of solution

Reliable standard metadata management
To guarantee domain consistency of a term by using a classification term. By ensuring consistency of expression through similar and forbidden word management, reliable standard dictionary management is possible. It also ensures data integrity through data quality degradation and impact queries.
Systematic DBMS object management
Enables ongoing validation through corporate DBMS catalog collection and DBMS VS Standard/Model GAP analysis. In addition, DBMS object change history management is useful.

Characteristic of SMETA	Specifics
Data standard management	Company-wide word, domain, term registration and management domain group management, code lookup Banned word/similar word management, term dictionary registration and management
Data model management	Registering and managing subject areas, registering and managing models such as entities and properties ER-Win model concatenation
Managing databases	DBMS tables, DBMS index registration and management Automatic creation of DDL and objects System DBMS Gap Analysis and Statistics
Other support tools	Metadata Request and Approval Process Standardized support tools, announcements, and integrated search Eclipse Terms Search and Use Tools Plug-in

SFLOW

(Smart Data Integration)

SFLOW, which combines B2EN's data processing technology and know-how, is a solution for data collection and integration. It provides a data-driven business framework by easily and quickly collecting various types of data within and outside the enterprise and providing it to business systems and data analysis systems.

Benefits of solution

Configuration
It guarantees development productivity and consistent quality by applying a GUI-based setting method rather than a programmatic method.
Overall
It supports protocols such as HTTP, FTP, and JMS and provides various types of DB, File, and sensor data collection functions.
Realtime
By providing a real-time monitoring environment centered on dashboard and topology map, it is possible to quickly identify failures and establish a response system.
Enhancement
The value of data can be expanded through the big data platform direct linkage function for collected data.

Characteristic of SFLOW	Specifics
Service	Supports both HTTP and FTP protocol service methods and dedicated message communication methods between SFLOW agents Message relay enables online data processing even in network separation environments
Process	Provides a combination function between components to meet various data processing requirements Process design, version management, runtime distribution capabilities
Monitoring	Provides integrated monitoring through topology map-dashboard-processing history-detailed tracking Provides various alarm functions so that operators can quickly recognize and respond to failures
Remote Control	Distributed agent control and various inquiry functions provided by central system operator Providing patches and upgrades through smart updates

SPORTAL

(Smart Data Portal)

A data utilization–centric portal that seamlessly supports the entire data lifecycle—from search and discovery to request and practical use of enterprise data assets. By integrating metadata, data quality, catalog, and lineage information, the portal enhances accessibility and usability of enterprise-wide data assets.It enables users to clearly identify the data they need based on data flows and relationships, providing a transparent and connected data environment.

Benefits of solution

Unified Search and Discovery Across Enterprise Data Assets
Provides integrated search and related asset discovery across distributed enterprise data assets—including columns, tables, dashboards, and reports—enabling users to quickly and easily find the data they need.
Informed Decision-Making Based on Metadata, Quality, and Lineage
Integrates technical (IT) and business (Biz) metadata, data standards, quality information, and lineage information into a unified Single View. Enables users to clearly understand data meaning, origin, and reliability at a glance, supporting informed decisions on data usability.
Seamless Data Utilization from Search to Approval
Handles data usage requests and approval workflows directly within the portal, ensuring a consistent and streamlined process.Allows users to complete the entire journey—from search to request, approval, and utilization—within a single system.

Characteristic of SPORTAL	Specifics
Enterprise Data Catalog at a Glance	Integrates and manages distributed enterprise data assets—such as databases, ETL, reports, and dashboards—by category, providing a clear overview of data assets. Combines IT and business metadata, quality information, and lineage to enable intuitive understanding of data meaning and reliability.
Integrated Search and Context-Aware Discovery	Supports keyword and natural language search to quickly find relevant data assets. Uses visualized lineage to explore related data and impact relationships.
Intuitive Enterprise Data Map	Visualizes data structure and scale through Tree Map charts for quick insight into distribution and characteristics. Provides drill-down views by system, resource, and asset type for detailed exploration.
Role-Based Personalized Dashboard with User-Centric UI/UX	Provides role-based dashboards with recently viewed items, favorites, my assets, and recommendations. Centralizes user activities—requests, approvals, comments, searches, and registrations—within My Page for clear workflow visibility.
Structured Access Policies from Data Disclosure to Improvement	Ensures both data usability and security through department-, user-, and asset-level access control. Standardizes error reporting and feedback to systematically manage data issues and establish a continuous improvement cycle.
Integrated Ecosystem for Data, Analytics, and AI	Integrates with data management solutions such as SMETA and SDQ to maintain catalog consistency. Supports scalable integration with ETL, BI, analytics, and AI systems to expand utilization.

HYPERGLORY

(AI Knowledge Management Platform)

An enterprise knowledge platform that integrates and manages diverse data sources—including documents, reports, emails, and relational databases—across the organization.Powered by Retrieval-Augmented Generation (RAG), it retrieves relevant information and enables AI to understand context, providing recommendations, insights, and decision support.The platform streamlines workflows, improves operational efficiency, and enhances agility in dynamic business environments.

Benefits of solution

High-Quality Responses Powered by Industry Knowledge
AI trained on industry-specific knowledge and business context delivers accurate and natural responses tailored to each domain.
Business-Tailored AI Implementation
Enables flexible system design tailored to diverse use cases, including Q&A chatbots, knowledge management, and training support.
Knowledge-Based Decision Automation
Automates processes from policy and regulation review to summarization, insight generation, and context-aware recommendations—reducing risk and enhancing productivity.
Role-Based Access Control (RBAC)
Strengthens security through RBAC-based policies and data-level filtering, enabling granular access control.

Characteristic of HYPERGLORY	Specifics
On-Premises AI Deployment	Processes sensitive data internally to minimize external leakage risks. Enables secure AI adoption and operation in highly regulated environments such as finance and public sectors.
Flexible Data and Business Integration	Connects heterogeneous data—including documents, images, and relational databases—to enable easy access to the right data and support data democratization. Supports optimized pipelines tailored to departmental and business needs. Provides a scalable architecture adaptable to complex business requirements.
RAG Management for Non-Experts	Offers an intuitive, no-code UI. Enables easy data management without specialized expertise. Enhances operational efficiency through visualization and automation.
Custom Pipelines and Endpoints	Supports concurrent multi-pipeline operations to meet diverse processing needs. Allows custom functions for task-specific processing logic. Provides independent API endpoints per pipeline for seamless system integration.