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ORACLE BI PUBLISHER 11G/12C: FUNDAMENTALS

DOANH NGHIỆP CHÚNG TÔI ĐÀO TẠO

” Khóa học Oracle BI Publisher 11g: Fundamentals (chính hãng Oracle) dành cho doanh nghiệp, tập đoàn lớn, khối chính phủ, các ngân hàng tại Việt Nam ” 

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Đối tượng

Thời gian học

Số buổi

Số học viên

Doanh nghiệp

Linh hoạt theo 

doanh nghiệp 

40h

Tùy thuộc vào 

doanh nghiệp 

NỘI DUNG KHÓA HỌC

  • INTRODUCTION TO DAMA
    • What is data management and why is it critical.
    • What are the different disciplines of data management?
    • DAMA & the DMBoK 2.0, and its relationship with other frameworks (TOGAF/COBIT…).
    • Overview of available professional certifications focusing on DAMA CDMP.
  • DATA GOVERNANCE
    • What is Data Governance and why it is important. A typical data governance reference model.
    • The main data governance roles: owner, steward, custodian.
    • The role of the Data Governance Office (DGO) and its relationship with the PMO.
    • What is the difference between Data Governance and IT Governance, and does it matter?
    • Overview of the Data Management implications of a selection of other regulations.
    • The key steps that organizations can take to prepare for compliance with current and future regulations.
    • How to get started with data governance and sustaining and building data governance.
  • DATA LIFECYCLE MANAGEMENT
    • Proactive planning for the management of data across its lifecycle.
    • Differences between data life cycle and a Systems Development Lifecycle (SDLC).
    • Data governance touch points throughout the data lifecycle.
  • METADATA MANAGEMENT
    • What is metadata and why it is important?
    • Types of metadata, their uses and their sources.
    • Metadata and business glossaries. What is the connection?
    • How metadata provides the essential glue for data governance and metadata standards.
  • DG MINI PROJECT
    • Starting the Data Governance Program, what you must get in place early. How to produce a realistic business case for DG linked to business objectives?
  • DOCUMENT RECORDS & CONTENT MANAGEMENT
    • Why document and records management is important.
    • Taxonomy vs. ontology… what’s the difference.
    • Legal and regulatory considerations impacting records and content management.
  • DATA MODELING BASICS
    • Types of data models, their use and how they interrelate.
    • The development and exploitation of data models, ranging from enterprise, through conceptual to logical, physical and dimensional.
    • Maturity assessment to consider the way in which models are utilized in the enterprise and their integration in the System Development Life Cycle (SDLC).
    • Data modeling and big data.
    • Why data modeling plays a critical part in data governance and BP case study.
  • DATA QUALITY MANAGEMENT
    • The different facets of data quality, and why validity is often confused with quality.
    • The policies, procedures, metrics, technology and resources for ensuring data quality.
    • A data quality reference model and how to apply it.
    • Why data quality management and data governance are interconnected and case studies.
  • DATA OPERATIONS MANAGEMENT
    • Core roles and considerations for data operations.
    • Good data operations practices.
  • DATA RISK & SECURITY
    • Identification of threats and the adoption of defenses to prevent unauthorized access, use or loss of data and particularly abuse of personal data.
    • Identification of risks (not just security) to data and its use.
    • Data management considerations for different regulations, e.g. GDPR, BCBS239.
    • The role of data governance in data security management.
  • MASTER & REFERENCE DATA MANAGEMENT
    • The differences between reference and master data.
    • Identification and management of master data across the enterprise.
    • 4 generic MDM architectures and their suitability in different cases.
    • How to incrementally implement MDM to align with business priorities.
    • Statoil (Equinor) case study.
  • DATA WAREHOUSING, BUSINESS INTELLIGENCE & DATA ANALYTICS
    • What is data warehousing and business intelligence and why do we need it.
    • The major data warehouse architectures (Inmon & Kimball).
    • Introduction to dimensional data modeling.
    • Why master data management fails without adequate data governance.
    • Data analytics and machine learning and data visualization.
  • DATA INTEGRATION & INTEROPERABILITY
    • What are the business (and technology) issues that data integration is seeking to address?
    • Data integration and data interoperability – What’s the difference?
    • Different styles of data integration and interoperability, their applicability and implications.
    • The approaches and guidelines for provision of data integration and access.
  • DAMA CERTIFICATION-FIRST LEVEL
    • Students will have the opportunity to sit the CDMP Data Quality specialist exam at the end of this course to attain DAMA Certified Data Quality Professional designation and a credit towards attainment of a full CDMP at Practitioner or Master Level.

Upon completion of the course, participants will be able to:

  • Different categories of challenges
  • Appreciate concepts including lifecycle management, normalization
  • Dimensional modeling and data virtualization and appreciate why they are important
  • Understand the critical roles of master data management and data governance and how to effectively apply them
  • Understand the different facets (dimensions) of data quality and explore a workable data quality framework
  • Describe the major considerations for successful data governance and how it can be introduced in bite-sized pieces
  • Understand the different types of data models and their applicability
  • Attend the DAMA certification exam.

HỌC PHÍ

Khoá Đào Tạo Dành Cho Doanh Nghiệp

Học phí: Liên hệ

Số Điện Thoại: 0986.882.818

GIẢNG VIÊN TẠI INDA

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Ảnh Thực Tế

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  • Big Data Specialists
  • Sprint, Scrum Master ,  Project Lead, Agile Lead

Chúng tôi có hai hình thức học: Offline (tại nơi doanh nghiệp yêu cầu) và Online (Trực tiếp với giảng viên qua Team/ Zoom/ Google Meet) Theo yêu cầu của doanh nghiệp

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