What you’ll learn
- Master the core principles of data governance and the roles and responsibilities involved.
- Understand the DAMA-DMBOK framework and its importance in data management.
- Learn the structure and certification levels of the CDMP exam.
- Explore strategies for preparing and studying for the CDMP certification exam.
- Grasp the foundational concepts of data architecture, including logical and physical data models.
- Design scalable data systems that meet organizational needs.
- Gain a deep understanding of data modeling, including normalization and denormalization techniques.
- Develop expertise in data storage models, data retention, backup, and recovery strategies.
- Understand the principles of data security and how to mitigate risks in data management.
- Implement best practices for ensuring data quality and improving data integrity.
- Explore the concepts of master and reference data management and their role in data consistency.
- Learn the fundamentals of metadata management and how it enhances data accessibility and governance.
- Understand the role of data warehousing and business intelligence in strategic decision-making.
- Explore emerging technologies like AI and big data and their impact on data management.
- Dive into cloud data management and its benefits for scalable and secure data storage.
- Understand ethical data management practices and how to ensure regulatory compliance.
This course includes:
- 21 hours on-demand video
- 1 article
- 75 downloadable resources
- Access on mobile and TV
- Full lifetime access
- Certificate of completion
Description
This course offers an in-depth exploration of the core principles and frameworks surrounding data management, with a specific emphasis on preparing students for the CDMP (Certified Data Management Professional) certification. The course is designed to provide a comprehensive overview of the various aspects of data management, including governance, architecture, modeling, security, quality, and more. While the course encompasses the theory of these data management concepts, it also provides valuable insights into how they can be applied in real-world scenarios, making it an essential resource for those looking to deepen their understanding of data management or prepare for the CDMP exam.
Beginning with an introduction to the CDMP certification process, students will gain a detailed understanding of the certification levels, exam structure, and essential study strategies. This foundational knowledge not only prepares students for the certification itself but also provides a solid framework for comprehending the broader field of data management. In particular, students will appreciate the subtle focus on theoretical aspects that underpin data management, allowing them to explore the key concepts without the distraction of immediate hands-on applications.
The course delves into data governance, one of the most crucial pillars of effective data management. Students will examine the roles and responsibilities that come with governance, as well as the policies, procedures, and frameworks that support a strong data governance strategy. Understanding governance frameworks is essential for ensuring that data remains secure, accurate, and compliant with industry standards. Students will learn how governance ties into the overall architecture of data systems and how it forms the backbone of a sustainable data management strategy.
Next, the course takes a closer look at data architecture, providing insights into how data is structured, modeled, and managed across an organization. Key concepts such as logical versus physical data models and the principles of designing scalable data systems are explored in detail. Students will also study enterprise architecture and its integration with data management practices, which is crucial for organizations aiming to align their data systems with strategic business goals. This section encourages students to think critically about the theoretical models that shape modern data architecture and how these models can be adapted to meet an organization’s unique needs.
Data modeling and design are fundamental to ensuring that data is both useful and efficient in meeting organizational objectives. The course covers essential topics such as normalization, denormalization, and data relationships, providing students with the knowledge needed to design and optimize data models for various industries. In doing so, students will gain an understanding of best practices in data design, with an emphasis on conceptual, logical, and physical data models, further cementing their grasp of data management theory.
Students will also explore the intricacies of data storage and operations, including storage models, techniques, and policies for data retention, backup, and recovery. The importance of data security management is also highlighted, focusing on principles, policies, and strategies for mitigating risks and ensuring regulatory compliance. In today’s digital age, where data breaches and cybersecurity threats are constant concerns, understanding these security principles is vital for anyone working in data management.
Furthermore, the course covers essential topics such as data quality management, metadata management, and reference and master data management. Each of these areas contributes to the overall goal of maintaining high standards of data integrity, accessibility, and usability. By the end of these sections, students will be equipped with the knowledge to assess and improve data quality, manage metadata repositories, and ensure that master and reference data are handled efficiently.
As the course progresses, students will learn about data warehousing and business intelligence, which are critical for leveraging data in decision-making processes. The course also addresses emerging trends in data management, including the role of big data, artificial intelligence, and cloud technologies, which are reshaping the future of data systems.
In summary, this course offers a thorough examination of data management principles with a focus on preparing students for CDMP certification. Through its structured approach to theoretical concepts, students will build a robust foundation in data management, which can be applied to a wide range of professional settings. Whether you are new to the field or looking to formalize your expertise, this course provides the essential knowledge and tools needed to excel in the dynamic and evolving world of data management.
Who this course is for:
- Aspiring data management professionals seeking to earn the CDMP Associate certification.
- IT and data professionals looking to enhance their knowledge of data governance, architecture, and security.
- Individuals transitioning into data management roles who want a comprehensive understanding of key principles.
- Business analysts and data analysts aiming to improve their data modeling and quality management skills.
- Project managers and team leads overseeing data-driven projects and seeking to improve data strategies.
- Recent graduates in IT, computer science, or business-related fields who want to specialize in data management.
- Professionals interested in staying updated on emerging trends like AI, big data, and cloud technologies in data management.
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