1.Building a constant data quality monitoring system for Korean Intellectual Property Office

Customer Issue & Requirement

  • Increased error rates due to the increased system complexity and a wide variety of data types.
  • A high-quality data providing system is needed
  • External service data verification is needed due to the increasing number of public service



  • Built a constant data quality monitoring system centered on an integration repository.

– Built a Meta System, Quality System, and Impact System

  • Established a data governance system

– Data management policy (data standards, data quality)
– Data management process
– Data management organization



  • Securing the reliability of public data service
  • Gaining a competitive advantage over the global data quality competition by systematic data management
  • Building a high-quality data providing system to deal with domestic and global data


2.Building a data quality management system for Samsung Fire & Marine Insurance

Customer Issues

  • A developer reads DB catalog information and manually inserts.
  • If a user wants to re-execute a job, he/she must register it as a new schedule.
  • It must be executed by registering a schedule per a business rule.
  • Registering a diagnostic schedule by column basis for profiling



  • Automatic extraction(table, column, domain, code…) periodically or non-periodically after registering the target DB connection information(ID, PW…)
  • For a business rule, one or more rule set for one job is registered and executed. For resuming, it is managed by execution frequency.
  • For profiling, a task is categorized by table.
    – Column analysis, pattern analysis, date analysis, code analysis
  • Monitoring the analysis task, checking the performance assessment and the results



  • Performing pre and post data quality verification
  • Building a management system for operations, measurement, and improvement
  • Automating meta data collection/ Diagnostic job management/ Applying a diagnostic rule set