Data Governance with Databricks
Skills:
Data Literacy50%
Key Takeaways
Implementing data governance using Databricks with lakehouse architecture and machine learning models
Original Description
Databricks is a cloud-based data engineering tool used to process and transform large amounts of data and explore the data through machine learning models. It combines data warehouses & data lakes into a lakehouse architecture.
Data governance is a broad approach that comprises the principles, practices, and tools to manage an organization’s data assets throughout its lifecycle. A data governance strategy allows organizations to make data easily available protecting their data from unauthorized access, and ensuring compliance with regulatory requirements.
This course provides 4 hours of training videos which are segmented into modules. The course concepts are easy to understand through lab demonstrations. In order to test the understanding of learners, every module includes Assessments in the form of Quizzes and In-Video Questions. A mandatory Graded Questions Quiz is also provided at the end of every module.
Candidate should have hands-on knowledge of the Databricks platform with the basic knowledge of AWS services. This course is tailored for professionals seeking to establish a strong foundation in data governance, fraud detection, and prevention strategies. By the end of this course, you will be able to:
-Understand the benefits and features of Databricks on AWS.
-Demonstrate Data Cleansing Pipelines in Databricks.
-Analyze Data Access Control Models and Data Privacy Regulations.
-Elaborate Data Lineage and Data Versions in Databricks Pipelines
Watch on External: Coursera ↗
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