Data Governance with Databricks

Instructor: Whizlabs Instructor

What you'll learn

  •   Learn to integrate AWS with Databricks.
  •   Learn Data Lineage, Databricks Tags and Data Catalog in Databricks.
  •   Learn to implement RBAC (Role-Based Access Control) in Databricks.
  • Skills you'll gain

  •   Personally Identifiable Information
  •   Data Management
  •   Data Warehousing
  •   Data Architecture
  •   Data Capture
  •   Extract, Transform, Load
  •   Role-Based Access Control (RBAC)
  •   Data Cleansing
  •   Metadata Management
  •   Data Pipelines
  •   Data Migration
  •   Data Security
  •   Data Lakes
  •   General Data Protection Regulation (GDPR)
  •   Databricks
  •   Amazon Web Services
  •   Data Governance
  •   Data Quality
  • There are 4 modules in this course

    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

    Data Classification Techniques and Data Quality Management

    Data Privacy and Security

    Data Governance in Data Pipelines

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