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Certificate (Data Science)

Preparing for the Data Architect Associate (DAsP) Certification

The Data Architecture Junior Professional (DAsP) is a certification that certifies expertise in data management and design, covering data modeling, architecture design, data standardization, etc. This preparation course systematically learns from basic concepts of data architecture to practical application cases, and strengthens problem-solving skills through practical exercises. It is suitable for beginner learners who want to grow as data professionals.

(4.6) 7 reviews

46 learners

  • sdj0831
데이터모델링
기출
자격증
시험
Data Architecture Semi-Professional
Architecture
Big Data
DBMS/RDBMS
Data literacy

Reviews from Early Learners

What you will learn!

  • Warrior Architecture

  • Data Requirements Analysis

  • Data Standardization

  • Data modeling

Data Architecture Semi-Professional (DAsP) 🚗

In this course, the three main topics you will learn in the Data Architecture Associate program focus on understanding the fundamentals of data architecture and developing the ability to perform data management and design. Accordingly, I will introduce the following three key learning areas.

💡Write a concise title that catches the eye

  • "Designing the Framework of Data: Complete Mastery of Data Architecture"

    • Emphasizes that you can master the core concepts and design methods of data architecture.

  • "First Steps as a Data Expert: New Opportunities Opening with DAsP Certification"

    • It emphasizes that obtaining certifications is the beginning of the path to becoming an expert.

  • "Design the World with Data: From Data Requirements Analysis to Modeling"

    • It suggests the scope of learning centered on content applicable to practical work.

  • "Everything About Data Standardization: The Secret to Building Successful Architecture"

    • We emphasize the importance of standardization so that you can feel its practical value.

  • "Technology for Connecting Data: Know-how in Enterprise Architecture Design"

    • It provides an opportunity to learn about the importance of data from an enterprise-wide perspective.

You'll learn this kind of content

1⃣Data Architecture Concepts and Principles

  • Definition and Necessity of Data Architecture:

    • Data architecture is a blueprint that designs the structure, management, integration, and utilization of data within an organization.

    • Data strategy, understanding data utilization methods linked to business objectives.

  • Key Components of Data Architecture:

    • Data Modeling: Designing data entities, attributes, and relationships.

    • Data Governance: Quality management, security, and regulatory compliance of data.

    • Data Storage: The roles and design of storage systems such as databases, data warehouses, and data lakes.

  • Data Architecture Design Principles:

    • Modularity and Reusability.

    • Scalability and Flexibility.

    • Security and Compliance.

2⃣Data Modeling and Database Design

  • Data Modeling Basic Concepts:

    • Conceptual Data Modeling: Visual representation of high-level business requirements.

    • Logical Data Modeling: Converting business requirements into logical structures.

    • Physical Data Modeling: Concrete design for database implementation.

  • Database Design and Management:

    • Relational Database (RDBMS) Design and SQL Utilization.

    • Characteristics and examples of non-relational databases (NoSQL).

  • Normalization and Denormalization:

    • Data duplication minimization and performance optimization.

  • Data Integration:

    • Understanding Data Migration and ETL (Extract, Transform, Load) Processes.

3⃣Data Management and Governance

  • Data Quality Management:

    • The importance of data accuracy, completeness, consistency, and timeliness.

    • Data cleaning and quality inspection techniques.

  • Data Governance and Policy Development:

    • Define data ownership (Role), responsibility (Responsibility), and usage policy (Policy).

    • Data security and privacy protection (e.g., GDPR, CCPA, etc.).

  • Metadata Management:

    • The definition and role of metadata.

    • Data catalog and data lineage tracking.

  • Data Security and Privacy:

    • Data encryption, access control, and breach response measures.

💡Introduce the learning content with representative keywords.

1. Data Architecture

  • Methodologies and strategies for designing data structure and management systems.

2. Enterprise Architecture

  • A system that comprehensively manages and optimizes IT and data resources across the entire organization.

3. Data Requirements Analysis

  • The process of collecting, analyzing, and documenting user and system requirements to connect them to data design.

4. Data Standardization

  • A methodology for establishing and maintaining standards to ensure data consistency and quality.

5. Data Modeling

  • Techniques of conceptual, logical, and physical modeling and database design through these approaches.

6. Reference Model

  • A standardized model used in architecture design.

7. Data Governance

  • A system that manages data quality, security, policies, and other aspects.

8. Metadata Management

  • Systematically manage information about data to maximize data utilization.

9. Data Quality Management

  • Activities and tools to ensure data accuracy, consistency, and completeness.

10. Data Integration and Connectivity

  • Technology that integrates data from various sources to ensure mutual connectivity.

11. Understanding Big Data Platforms

  • Large-scale data processing system architecture and design.

12. Data Security and Privacy

  • Data access control, encryption, and privacy protection policies.

Pre-enrollment Reference Information

Practice Environment

  • Operating System and Version (OS): Not applicable

  • Tools used: None

  • PC Specifications: Basic specification PC with internet access capability

Learning Materials

  • Learning materials provided: PPT, cloud links, text, source code, sample problems, etc.

  • Volume and Capacity: Learning materials provided for each section

Prerequisites and Important Notes

  • No prior knowledge is required.

  • Having middle and high school level mathematics knowledge and Python programming experience can be helpful for taking the course. However, since all the foundational content needed for the course is explained, there will be no problem if you take it with enthusiasm.

  • The copyright of this course belongs to DFACTUP Co., Ltd., and unauthorized distribution and reproduction are prohibited. The learning materials are also copyrighted and may not be used for purposes other than personal learning.

  • This entire lecture is conducted with AI voice.

Recommended for
these people

Who is this course right for?

  • Entry Level Data Analyst

  • IT Developers, Data Analysis Beginners

  • Data-based system related personnel

  • IT Planning and Consultant

Hello
This is

208

Learners

31

Reviews

10

Answers

4.3

Rating

10

Courses

Digital Spec Up(이하 (주)디펙업)은 IT 및 DT 관련 과정들을 전문으로 제작 및 개발하는 콘텐츠 기업입니다.

IT 관련 분야로 취업에 도움을 드리기 위해 자격증 과정을 개설하여 운영하고 있으며, 앞으로도 다양한 IT 자격증 관련 과정을 포함한 IT 부분의 특화된 콘텐츠를 지속적으로 제공해 드릴 예정입니다.

디팩업의 대표인 저는 20년간 IT보안, ISP 및 PI 컨설팅과 IT 기획 업무를 주로 해왔고, 주로 국제 공인 자격증을 비롯한 다수의 IT 관련 자격증을 갖고 있습니다.

주요 학력

  • 선문대학교 산업공학과 졸업

  • 성균관대학교 경영대학원 MBA(경영학) 졸업

주요 경력

  • 전) (주)세이퍼존 정보보안기술연구소 정보보안컨설팅 / 대리

  • 전) (주)인젠 NCA보안지원팀 정보보안 파트 위탁 운영 / 대리

  • 전) (주)제이티 경영혁신실 IT기획 및 정보보안 총괄 / 과장

  • 전) LS글로벌(주) IT기획팀 과장

  • 전) (주)코어인포텍 컨설팅 사업본부 / 부장

  • 전) 셀레스티카 코리아(유) IT기획팀 / 차장(팀장)

  • 전) (주)얌테이블 애자일 그룹 R&D팀 / 부장(팀장)

  • 전) KTDS 보안사업팀 / 부장

  • 전) 천재교과서 ISP 및 PI 컨설팅 프로젝트 참여(프리랜서)

  • 전) (주)컨셉위드인사이트 컨설팅사업본부 / 이사

  • 현) (주)디펙업 대표 강사

주요 강의 경력

  • 현) KG에듀원 학점은행 경영학 교강사

  • 현) 고려아카데미 컨설팅 이러닝 과정 IT 및 경영 분야 온라인 튜터

  • 현) 멀티캠퍼스 이러닝 과정 IT 및 경영 분야 온라인 튜터

  • 현) 온캠퍼스 이러닝 과정 IT 및 경영 분야 온라인 튜터

  • 현) IT분야 내용전문가로 활동 중(SME) - 정보보안, 데이터 아키텍처, 데이터 거버넌스, 사물인터넷 분야

  • 현) (주)디펙업 IT 자격증에 관련된 온라인 콘텐츠 제작 및 개발

보유 자격증

  • CIW Adminstrator

  • CIW Security Analyst

  • CompTIA Network+ Pro

  • CompTIA Server+ Pro

  • CompTIA I-Net+ Pro

  • LPIC Level 2

     

  • 정보처리 기사, 정보보안 기사, 빅데이터 분석 기사

주요 저서

이기적 정보보호능력검정(TOLIS) 수험서 집필 중(영진닷컴-2025년 11월 출간 예정)

개인 유튜브 채널(AI 및 DT 관련 이러닝 무료 동영상 강좌) : www.youtube.com/@신동주-s1b

개인 유튜브 채널(AI 시대의 최신 트렌드): www.youtube.com/@바이트탐정

디펙업 카페: https://cafe.naver.com/digitalspecup

Curriculum

All

22 lectures ∙ (5hr 34min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

7 reviews

4.6

7 reviews

  • djccnt15님의 프로필 이미지
    djccnt15

    Reviews 18

    Average Rating 5.0

    5

    100% enrolled

    • sdj0831
      Instructor

      Congratulations on completing the course. I promise to meet you again with even more upgraded lectures in the future. Thank you.

  • aqaok120905님의 프로필 이미지
    aqaok120905

    Reviews 1

    Average Rating 4.0

    4

    100% enrolled

    • montreal3506523님의 프로필 이미지
      montreal3506523

      Reviews 1

      Average Rating 4.0

      4

      32% enrolled

      • bradpitt님의 프로필 이미지
        bradpitt

        Reviews 5

        Average Rating 3.8

        5

        32% enrolled

        The detailed explanations and smooth progression look good.

        • sdj0831
          Instructor

          Hello learner. Thank you for your good feedback. I sincerely hope that this course will be helpful to you. I will continue to do my best to help learners with high-quality courses that are helpful and easy to understand. Thank you.

      • sdj0831님의 프로필 이미지
        sdj0831

        Reviews 7

        Average Rating 5.0

        5

        18% enrolled

        If students have any questions or inquiries they need, please feel free to leave your comments anytime and I will kindly answer them. Thank you.

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