Metadata management tools established in 150 places including public institutions and financial fields

By consistently organizing metadata information such as data standards, data models, databases, and data flows, you can improve data understanding and work productivity.

The need for data standardization

In information systems, the term is the name of data used in screens, programs, databases, etc., and is often referred to as attributes. Standardizing the meaning, format, and representation of data in information systems is very important in terms of maximizing system integration and information sharing effects.

By defining information items and designing data structures based on data standardization, inefficient operations such as data mapping and change between systems can be minimized. Data standardization can be said to be the starting point for establishing the foundation of the information system, as it is possible to quickly and accurately check the impact of data changes on the information system due to business changes.

Excellent user accessibility and convenience based on the web

It is web-based and has excellent user accessibility and management convenience.

There is no need to install ActiveX and Flash, and various convenient functions such as various OS and WAS support are provided.

Introduced to a number of large-scale next-generation projects and linked to a pan-government data platform

Currently, it has the largest and largest number of next-generation application cases in Korea, and its technology has been recognized by being listed in the 2019 GS Certification Grade 1 and Gartner Newsletter.

It also provides the ability to link with the government-wide data platform. It is possible to collect data from each institution, link central metadata and metadata, and apply for and extract source data.

System configuration diagram

  • 누구나 쉽게 당사의 제품을 이용하여 데이터표준, 데이터모델, 데이터베이스, 데이터흐름 등의 메타데이터 정보를 일관성 있게 정리하여 데이터에 대한 이해도와 업무생산성을 향상시킬 수 있습니다.

WiseMeta™ main features

  • 01
    Data standard management
    • Manage data standards such as standard words, domains, valid values, standard items, synonyms and non-words
    • Management of standard dictionary for each system
    • Automatic segmentation and recommendation of standard items
  • 02
    Data model management
    • Subject area, data model management (various verification functions such as compliance with standard dictionary)
    • Manage index and partition information
    • Linking modeling tools (ER-WIN, DA#, etc.)
  • 03
    Database Management
    • Support for DB reflection of data model (DBA support)
    • Create DB reflection script (DDL) and collect DB catalog information
    • Development, test, verification, operation DB reflection script transfer management
  • 04
    Impact Analysis
    • Mapping definition, data flow management
    • Analysis of utilization between metadata
    • Standard compliance rate, gap analysis between standard/model/DB
  • 05
    Pan-government data platform linkage
    • Collect institutional metadata
    • Central meta and metadata linkage
  • 06
    AI-based standardization
    • Identify the characteristics of data through exploratory analysis
    • Automatic domain determination for standardization
    • Recommendation of standard terms through similarity analysis

WiseMeta™ Key Features

  • Maximize efficiency by providing data lifecycle management processes
    • Data lifecycle management such as definition of data standards (standard terms, words), modeling work using a dictionary and conformity review, and DB reflection by providing DDL scripts can be performed in one process, maximizing work efficiency.
  • Provide metadata management efficiency and convenience through linking with related systems
    • Developed based on JAVA, it can be linked with other solutions such as various development frameworks (provided standard dictionary information), messengers, mail systems (messages or mails are sent when payment is completed), and impact analysis tools, and improves the efficiency of metadata management. .
  • Metadata change control possible through the approval process
    • In order to understand and control the impact of metadata changes, we provide request and payment functions (by individual and group) for each registration request menu in the system. Data quality can be improved by controlling new/modified/deleted metadata.
  • Automated data standardization by applying AI algorithm
    • Efficiently manage company-wide metadata through automated data standardization, such as automatic data domain identification and recommendation, and standard item recommendation through similarity analysis.