데이터 활용 극대화를 위한 데이터 플랫폼 구축전략 ENSTACK | DataOps Strategy for Maximizing Data Literacy

    데이터 플랫폼 구성 전략

    Dataops Strategy
    New paradigm of data management

    From data development to operation and utilization
    It supports flexible collaboration orchestration
    between data management processes and organizations.

    체계적인 데이터 관리
    Supply high-quality data through systematic data governance system

    Enterprises introduce the latest IT technologies such as AI, RPA, and ML, and provide complex on-premise and various types of cloud services.
    We are actively introducing new technologies and infrastructure of the company.
    Based on this, we expect successful business performance using data, but continuous business value creation is impossible with one-off management.

    A harmonious orchestration of organizations, processes, and technology is required to utilize high-quality data optimized for business.

    The DataOps strategy, which can ideally manage smooth communication between the data management organization and the consuming organization,
    and is the optimal strategy to solve the problems of data management and utilization that companies have been trying to solve so far.

    DataOps Strategy It refers to the orchestration of people, processes, and technology to quickly deliver reliable, high-quality data to users.
    The main business of Encore Solution Center is software development and supply to provide a collaboration system
    between data management organizations and data utilization organizations.
    Maximizing Data Literacy Strategy Provides data utilization foundation for maximizing data literacy
    The Foundation for Data Aeetization
    Based on data assetization -
    core tasks and major
    management items
    • Data Identification – Standard / Non-Standard, Technical & Business Meta
    • Understanding Data – Conceptual Model / Logic Model / Physical Model (Structure)
    • Data life cycle validity / freshness / data flow
    • Data Quality – Diagnosis and Improvement / Impact Analysis
    • Data Ownership – Subject for quality control and data supply
    • Data Stewardship – Management Process
    • Data access – data consumption / retrieval and request
    Solutions
    • Data Modeling Tool (DATAWARE-DA#)
    • Metadata management solution (DATAWARE-META#)
    • Data quality management solution (DATAWARE-DQ#)
    • Application impact analysis solution (DATAWARE-AP#)
    • Data flow management solution (DATAWARE-DF#)
    • Data catalog and portal solution (DATAWARE-DP#)
    Prepare data combination
    Based on data combination -
    core tasks and major
    management items
    • Data Combined Space – Physical/Logical Data Lake
    • Data Combination Cost – Waste of unnecessary storage space
    • Data security level – Sensitive information access control and access history
    • Securing data freshness – cycle and method of obtaining the latest data
    Solutions
    • Data Migration Tool (DATAWARE-ETT#)
    • Data Virtualization & Logical Data Lake (DATAWARE-DV#)
    • Data operation management and control (DATAWARE-SQL#)
    Service
    • Building a big data platform ecosystem using open source and cloud services
    Sharing Data Basis
    Based on data sharing -
    core tasks and major
    management items
    • Data sharing and trading – data market store configuration
    • Data Serving – Customer Application Request Data Supply API
    • Data Harvest – external data catalog collection and sharing
    • Data Preprocessing – Data Preparation / Cleansing / Filtering
    • Data Processing and Analysis – Citizen Data Scientist / Professional
    Solutions
    • DATA HARVEST-Market Store
    • Data Preprocessing (DATA HARVEST – Data Preparation)
    • Heterogeneous data combination and data virtualization (DATAWARE-DV#)
    • Data visualization and analysis (DATAWARE-DS#)
    A data utilization platform based on data governance
    that enables data-based decision-making In order to maintain high-quality data, Overall data management should be done.
    Data governance for data management is the data management process
    It must be organically linked and through data management organizations, processes,
    and automation tools and solutions.
    By constructing the foundation, high-quality data assets can be secured.
    Full-Stack solution for data management and utilization, DATAWARE™ Data standard, model, structure, data performance, application impact analysis, data quality, data
    implementation and flow management, metadata management, data virtualization, data catalog
    through an integrated repository-based data management system that facilitates information
    exchange between data management solutions and data portal, systematic integrated data full-stack
    solution for compliance response can maximize customer's data management and utilization system.
    • Data Modeling Tools DA# systematizes data structures and designs and implements the entire process of data architecture.Model the data architecture you manage and management solutions.
    • Data modeling and quality diagnosis support package solution DA#_DQ Edition is for data modeling andAs a package solution capable of quality diagnosis, it supports companies as well as public institutions to respond to public data quality diagnosis level evaluation.
    • Meta Data Management Solution META# is a tool that supports consistent control and management of all stages of data structure through functions such as data standard management, data structure management, DBMS information management, and data meta impact analysis.
    • Data Quality Management Solutions DQ# is a data quality management solution that systematically manages quality issues such as inaccuracy, redundancy, and inconsistency of corporate system data from a company-wide perspective.
    • Application Impact Solution AP# analyzes the mutual influence of database and applicationIt supports application change, quality control and maintenance system.
    • Data flow management solution DF# is a data flow analysis solution that comprehensively collects and analyzes complex enterprise data structures to comprehensively track the flow of systems and data, which are important assets of the company, and manages them systematically and efficiently.
    • Data integration Solution ETT# extracts, transforms, loads andIt is a data migration tool that effectively and reliably handles verification and provides corporate data to the necessary elements in a timely manner. It supports not only data migration of corporate systems but also cloud migration.
    • Data Operations and Security Management Solutions SQL# provides access rights, history and control, and data masking for users accessing data consistently in data management policy-governance policy, and provides enterprise applications andIt is a solution that manages SQL accessing commercial SW DB.
    • Data virtualization solution DV# is a distributed database, It is a virtualization solution that integrates files and big data into a virtual data layer in a separate memory space and supports the establishment of an environment that can utilize the latest data in real time.
    • Data portal solution DP# is an efficient corporate data portalSolutions for deployment, enabling easy data discovery, request, analysis and utilization
    DATAWARE™ Full-Stack Solutions for Data Management and Utilization
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