Курс
Data Management in Databricks
БазовыйУровень навыков
Обновлено 05.2026
DatabricksData Management3 ч10 видео31 Упражнение2,350 XP5,571Справка об успешном завершении
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Build a Strong Foundation with Delta Lake
This course equips you with the skills to manage data effectively in Databricks, leveraging tools like Delta Lake and Databricks’ Data Explorer. You'll explore foundational concepts such as managed and unmanaged tables and how they handle storage and lifecycle while diving into advanced Delta Lake features like ACID transactions, schema enforcement, and time travel. These techniques ensure data consistency and reliability, laying the groundwork for robust data workflows.Optimize Workflows with Views and Temp Views
You'll also learn to create and manage views and temp views to optimize data processes. Persistent views allow you to save query logic for repeated use across sessions, streamlining workflows and boosting efficiency. Temp views, on the other hand, provide a lightweight solution for quick, session-specific tasks. Practical examples demonstrate how each can be applied to enhance data accessibility and organization, making them invaluable tools for crafting efficient and flexible solutions.Secure and Govern Your Data with Confidence
Finally, you'll harness Databricks’ Data Explorer to preview, analyze, and secure datasets. From assigning table ownership to managing access rights, you'll gain a comprehensive understanding of governance best practices. Special emphasis is placed on securely handling Personally Identifiable Information (PII) with compliance-focused strategies. Through hands-on exercises, you'll develop the expertise to maintain secure and optimized datasets, ensuring your data remains accessible, well-managed, and protected in any scenario.Необходимые условия
Introduction to Databricks1
Introduction to Delta Lake
This chapter explores table management in Databricks, focusing on managed vs. unmanaged tables and how they handle storage and lifecycle. You'll learn to create and refresh persistent views and dive into Delta Lake features like ACID transactions, schema enforcement, and time travel for reliable data management. You will also gain a deeper look into the mechanics of data organization and access within Databricks.
2
Working with Tables in Databricks
This chapter delves into creating and managing views and temp views in Databricks. You'll explore how persistent views save query logic for reuse across sessions, while temp views are suited for quick, session-specific tasks. The discussion also highlights practical scenarios where each type can enhance efficiency and streamline data handling.
3
Data Exploration and Security
In the final chapter, you’ll explore how to use Data Explorer to preview, analyze, and secure datasets. The content covers table ownership, responsibilities, and governance best practices. It also dives into managing access rights and securely handling Personally Identifiable Information (PII) with compliance-focused strategies and practical exercises.
Data Management in Databricks
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