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Courses > Modeling
Model-based data governance and data middle platform construction
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Zu Tao
Founder of Pitaya Software Engineering
 
Time Location: Beijing, Shenzhen and Shenzhen open classes Based on registration
Course Cost：1300 $/Person
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Internal Training: You can customize internal training according to the needs of the enterprise.

Authentication Method:
Understand the competency model before training.
Ability evaluation after training:
  • Online Examination
  • Ability Analysis, give learning suggestions
    • The qualified person shall be issued a certificate as proof of vocational skill qualification

    Many enterprises hope to realize enterprise digital empowerment through data governance: through data governance, the existing data assets are sorted out, the quality of data is optimized, and data services are provided through the data middle platform to provide better support for the current business. Data governance is faced with a lot of data, and the first task is to clearly describe the existing data and its related businesses and systems. Data models, business models, and system models are undoubtedly important supports for data governance. This course focuses on the models to be established in data governance, the relevant modeling standards, and how to use models to diagnose problems, architecture design, and platform implementation. The course will discuss the effective application of data governance models with participants in the form of case studies.

     
    Training Features:

    • Senior expert teaching, interactive case teaching, and actual combat simulation project operation
    • Master the modeling techniques of data governance through hands-on exercises
    • Combining theory and practice, focusing on the explanation of cases
    • Throughout the case explanation, the students learn by doing, which is specific and profound.
    • Consult the cases proposed by the trainees to guide the analysis and design.

    Training Goal:

    By the end of this course, participants should be able to:
    • Understand why model-based data governance is essential
    • Learn what model-based data governance has to offer
    • The modeling environment needed for data governance
    • Data governance: Investigation and modeling of the current state of data
    • Data Governance: Business Modeling
    • Data Governance: Data modeling
    • Data Governance: Systems Modeling
    • Data Management Maturity Assessment
    • Data architecture design and modeling
    • Modeling of data management systems
    • Data middle platform design
    • Data governance implementation planning

    Training Target： system engineers, demand researchers, development engineers, technical solution personnel
    Student Foundation: Experience in data analysis or data management
    Teaching Method: Customized Course + Case Explanation + Group Discussion, 60% Case Explanation, 40% practice exercise
    Training Content: 2 Days
    Topic Course Schedule
    Data governance overview Objectives of Data Governance Top-level Architecture of
    Data Governance Core Content of
    Data Governance DAMA Data Governance Engineering System Reference:
        • Data Architecture Management
        • Data Development • Data Operation Management
        • Data Security Management
        • Master Data and Reference
    Data Management
        • Data Warehouse and Business Intelligence Management
        • Document and Content Management
        • Metadata Management
        • Data Quality Management Current Challenges of
    Data Governance Trends in
    data governance
    An overview of model-based data governance Why Model-Based Data Governance What models are needed for
    data governance:
        • Business model: a business application view of the data
        • Data model: business data, master data, underlying data, metadata
        • System model: storage data and interactive data flow Workflow for
    Model-Based Data Governance:
        • Data, Investigation of related business and system status
        • Data, business and system status modeling
        • Data problem diagnosis
        • Data governance architecture design
        • Establishment of data management system
        • Data platform design
    Data governance implementation planning
    The modeling environment needed for data governance Build an enterprise-level model library Model Center :
        • Model Library Structure Creation
        • Model Library User Account and Permission Configuration
        • Model Library Multi-person Access Security Policy Configuration
    Modeling Tools EA :
        • Business Modeling
        • Data Modeling
        • System Modeling
        • Model Tracking
    Model Publishing Tool web EA :
        • Model-Based Publishing and Model Browsing
        • Model-Based Data Management
        • Model-Based Data Quality Evaluation
        • Model-Based Change Management
    Model Management Platform iSpace :
        • Data Governance Modeling Guide
        • Data Model Library Management
        • Team Collaboration of Models
    Model association analysis and tracking
    Data governance: Investigation and modeling of the current state of data What are the contents of the data status investigation Methods of
    data status investigation
    How to build a model in the data investigation stage
        • Business model
        • Data model
        • System model
    Model-based data problem diagnosis method
    Data Governance: Business Modeling Data Governance Perspective of Business Modeling What to focus on
    in business modeling: Business Data Map Content and form of
    business data map
    How to conduct business modeling from a data perspective
    How to refine business data map from business model
    Establish a business data traceability view
    Data Governance: Data modeling Data Governance Perspective
    of Data Modeling Data Modeling Concerns: Data Maps Different Levels of
    Data Maps
        • Business Data Modeling
        • Master Data Modeling
        • Basic Data Modeling
        • Data Element Models
    Establish a traceability view of various data
    Data Governance: Systems Modeling Data Governance Perspective of System Modeling
    System Modeling Concerns: Data Map of the System Modeling Methods of
    System Data Map
    User Modeling and Functional Modeling
    System and Interface Modeling Data Flow Modeling Between
    Systems
    Establish a traceability view of the data flow of the system
    Data Management Maturity Assessment Refer to the data management maturity assessment model,
    establish the data management work model,
    define the maturity evaluation indicators, evaluate
    the data management work capability,
    and output the data management maturity capability report
    Data architecture design and modeling What is a data architecture What are the views of
    the data architecture
    How to build a metamodel of the data architecture
    How to design a user view of the data architecture
    How to design a logical view of the data architecture
    How to design a view of the data architecture implementation
    Modeling of data management systems What data management systems exist What are
    these data management systems The location of the
    data management system
    Use the data map to establish a data quality management system
    Use the data map to establish a data change management system
    Use the data map to establish a data security management system
    Data middle platform design What is a data middle platform, the difference between
    a data middle platform and a data platform, the boundary between
    a data middle platform and a data application, how does a
    data middle platform support data applications,
    how to establish a data middle platform based on data architecture,
    and implements the data management system into a data middle platform, and the construction and application demonstration of
    a data middle platform
    Data governance implementation planning Define the implementation goals
    of data governance Data Governance Phases and Milestone Definition
    Phase 1: Data Support
    Phase 2: Data Services
    Phase 3: Data Dominance Deliverables and Validation of
    Data Governance Implementation Tracking Management of
    Data Governance Data Architecture in
    Implementation, Change management of data policies
     
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    Consulting services: Database design and performance optimization
    Consulting objective Perform performance evaluation, design optimization and management optimization of customer database
    Scope of consultation Database performance evaluation, database structure optimization, data access SQL optimization.
    Consultation method Existing database investigation, problem diagnosis, performance evaluation
    The logical structure of the database is optimized, and the access SQL of the database is optimized.
    Establish database operation monitoring platform. Operation monitoring and optimization method guidance.
    successful case China Construction Bank, Agricultural Bank of China, Industrial and Commercial Bank of China, AVIC
    For more information:010-62670969， umlooo@hotmail.com