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[Certification Prep] Data Architecture Semi-Professional (DAsP)

This course is designed for those aiming to obtain the Data Architecture Semi-Professional (DAsP) certification. It provides a simple and systematic overview of essential exam topics, ranging from basic data architecture concepts to data modeling, data quality, and governance. The curriculum is structured to minimize complex theories and focus on frequently tested concepts, making it accessible for non-majors and beginners to learn without pressure. Build your fundamental skills in understanding data structurally while preparing for the DAsP certification.

(4.6) 8 reviews

59 learners

Level Beginner

Course period 12 months

Big Data
Big Data
Architecture
Architecture
Data literacy
Data literacy
Enterprise Architecture
Enterprise Architecture
Data Architecture Semi-Professional
Data Architecture Semi-Professional
Big Data
Big Data
Architecture
Architecture
Data literacy
Data literacy
Enterprise Architecture
Enterprise Architecture
Data Architecture Semi-Professional
Data Architecture Semi-Professional

What you will gain after the course

  • Enterprise 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 (DAsP) curriculum focus on understanding the foundations of data architecture and developing the ability to perform data management and design. Accordingly, we introduce the following three key learning contents.

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💡Try writing a concise and eye-catching title

  • "Designing the Backbone of Data: Mastering Data Architecture"

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

  • "The First Step for Data Professionals: New Opportunities Opened by DAsP Certification"

    • It highlights that obtaining the certification is the beginning of the path to becoming an expert.

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

    • Suggests the scope of learning, focusing on content that can be applied in practice.

  • "Everything About Data Standardization: Secrets to Building a Successful Architecture"

    • It emphasizes the importance of standardization so that you can experience its practical value.

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

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

What you will learn

1⃣ Data Architecture Concepts and Principles

  • Definition and Necessity of Data Architecture:

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

    • Understanding data strategy and data utilization plans linked to business goals.

  • Key components of data architecture:

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

    • Data Governance: Data quality management, security, and compliance.

    • 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.

2⃣ Data Modeling and Database Design 

  • Basic concepts of data modeling:

    • Conceptual Data Modeling: Visually representing high-level business requirements.

    • Logical Data Modeling: Converting business requirements into a logical structure.

    • Physical Data Modeling: Detailed 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:

    • Minimizing data redundancy and optimizing performance.

  • Data Integration:

    • Understanding data migration and ETL (Extract, Transform, Load) processes.

3⃣ Data 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 Establishment:

    • Defining data ownership (Role), responsibility (Responsibility), and usage policies (Policy).

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

  • Metadata Management:

    • Definition and role of metadata.

    • Data catalog and data lineage tracking.

  • Data Security and Privacy:

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

Notes before taking the course

Practice Environment

  • Operating System and Version (OS): N/A

  • Tools used: N/A

  • PC Specifications: A basic PC with internet access.

Learning Materials

  • Format of provided learning materials: PPT, cloud links, text, source code, example problems, etc.

  • Quantity and Capacity: Learning materials provided for each section

Prerequisites and Notes

  • No prior knowledge is required.

  • Having middle and high school level math knowledge and Python programming experience can be helpful for taking this course. However, since all the necessary basic content is explained within the lecture, there will be no issues as long as you take the course with passion.

  • The copyright of this lecture belongs to Deepackup Co., Ltd., and unauthorized distribution or reproduction is prohibited. The learning materials are also copyrighted and may not be used for any purpose other than personal study.

  • This entire lecture is conducted using AI voice.

Recommended for
these people

Who is this course right for?

  • Entry-level Data Professional

  • IT developers, data analysis beginners

  • Person in charge of data-driven systems

  • IT Planning & Consultant

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Curriculum

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22 lectures ∙ (5hr 36min)

Course Materials:

Lecture resources
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Reviews

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8 reviews

4.6

8 reviews

  • djccnt15님의 프로필 이미지
    djccnt15

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    • sdj0831
      Instructor

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

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    hws3207

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    • sdj0831
      Instructor

      I hope this lecture was helpful.

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    • bradpitt님의 프로필 이미지
      bradpitt

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      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.

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