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 with Databricks
Instructor: Whizlabs Instructor
Sponsored by Louisiana Workforce Commission
Recommended experience
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.
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There are 4 modules in this course
Welcome to Week 1 of Data Governance with Databricks course. This week, you will learn about Introduction to Databricks on AWS. Additionally, you will learn about the benefits and features of Databricks and AWS Integration.
What's included
9 videos3 readings3 assignments1 discussion prompt
This week, we learn Data Classification Techniques including Data Lineage and Impact Analysis and Metadata Management and Data Catalogs. We will also learn about the Data Profiling and Quality Assessment, Data Cleansing Techniques and implement Data Cleansing Pipelines in Databricks.
What's included
8 videos1 reading3 assignments
This week, we will learn about RBAC, Data Access Control Models and Data security policies in Databricks. We will also learn how to implement RBAC in Databricks, and Data Security Best practices.
What's included
10 videos1 reading3 assignments
This week, we will learn about Data Governance in Data Pipelines including Data Lineage in Data Pipelines, ETL/ELT processes, Data Versiong and Change Data Capture. We will also about Data Governance Best Practices and Tools including Continuous Improvement of Data Governance Processes and implementation and applying best practices in Data goverance.
What's included
14 videos3 readings3 assignments
Instructor
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