Data Governance with Databricks is a meticulously designed course offering comprehensive understanding and practical applications of data governance principles using Databricks. The course delves into the core components of data governance, such as frameworks, policies, roles, and regulatory considerations, along with data quality and metadata management. It is divided into two modules, with the first module focusing on fundamentals and the second on practical applications of Databricks for data governance.
Throughout the course, learners will grasp essential components of data governance, explore the significance of data governance in modern organizations, and understand Databricks' instrumental role. They will gain practical skills in data management, governance workflow design, data cataloging, security, and access control with Databricks. Real-world case studies and best practices will be examined to ensure effective, collaborative, and automated data governance.
This course is suitable for data professionals, data governance analysts, data stewards, IT managers, and individuals interested in improving their organization's data governance using Databricks. Whether beginners or experienced professionals, learners will enhance their skills in managing data, designing governance workflows, and ensuring security by drawing insights from real-world examples and best practices.
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The course comprises two modules: "Data Governance and Databricks - Fundamentals" and "Data Governance and Databricks - Application." The first module provides a comprehensive understanding of data governance and the role of Databricks, while the second focuses on practical applications of Databricks for data governance.
The "Data Governance and Databricks - Fundamentals" module provides a comprehensive understanding of the importance of data governance and the integral role of Databricks. Learners will explore the key components of data governance, including frameworks, policies, roles, regulatory considerations, data quality management, and metadata management. Real-world case studies and best practices are also covered to ensure effective data governance.
The "Data Governance and Databricks - Application" module focuses on practical applications of Databricks for data governance. Learners will gain insights into data management, governance workflow design, data cataloging, security, access control, data lineage, data discovery, collaborative data governance, and automation of governance processes. The module also examines successful data governance implementations and industry-specific use cases with real-world scenarios and best practices.
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