Customer Success Stories

SK Group

We conducted data governance-based Data Lake construction consulting to effectively share and utilize data distributed by SK Group affiliates from the perspective of group company integration.


  • Need to leverage the analytics shared infrastructure of the company and group and make data-driven decisions
    • Collect data from distributed legacy systems for each affiliate to leverage the company and group’s analysis sharing infrastructure and provide the necessary analysis data for data-driven decisions
    • Data Lake deployment provides a One Place environment, provides shared data between group companies, provides agile data analysis environments, enables data-based digitalization, secures data utilization sharing systems, and provides a self-service analysis environment
    • Need to provide Data On-Boarding services and Seamless analytics-based environments for efficient analysis and utilization of enterprise data


  • Data Lake Establishment Model Design
  • In order to efficiently manage SK affiliates’ data and establish a sharing system, a data lake policy establishment model is established by dividing it into data management areas, policies, processes, organizations, and roles
  • Development of data management plan for holding companies based on data governance
    • Based on Multi Repository Metadata (MRM), loading with data HUB is performed first for efficient data utilization
    • Defining an Industry Classification System for Sharing Information Between Affiliates and Affiliates and Mapping the Subject Areas of Affiliates’ Data
    • Define standards across group companies for joint use of data between relationships and map classification systems and data items
    • Establishing a data management framework and linking criteria definition, meta-management, standard management, and data profiling results to the service portal


  • SK Group Integration Data Lake Deployment
    • Spread Data-Driven Workforce on Integrated Data Lake
    • Support user capabilities through Data Lake’s use of analyzed data
    • Accelerate enterprise data access
  • Delivering a stable service experience
    • Provides data analytics services for increased utilization
    • Providing Data Ingestion/Collection Services
    • On-boarding service (as a service) is possible
    • Leverage Public Cloud’s Big Data Solution analytics environment
    • Building the Data Service Foundation