Implement Data Auditing with Azure Data Lake
This course will teach you data auditing, data masking, and encrypting data at rest and in transit on azure cloud. Planning secure endpoints, data retention, and archiving strategy we will be implementing in place using the azure cloud portal.
What you'll learn
Sensitive data masking should be of prime importance for efficient data governance models to be followed. In this course, Implement Data Auditing with Azure Data Lake, you’ll learn to apply efficient encryption, data masking, and secure endpoints over Azure Cloud Portal for specific services. First, you’ll explore how to design security for source data access. Next, you’ll discover designing security for data policies and standards. Finally, you’ll learn how to authenticate the service principle to mount data lake on Azure DataBricks. When you’re finished with this course, you’ll have the skills and knowledge of the importance of data masking, efficient encryption policies, management of key Vault, and policy-driven data lake architecture.
Table of contents
Course FAQ
In this course, you will learn about data masking, data encryption, how to secure endpoints over cloud, and the key benefits of endpoint security.
Before taking this course, you should be familiar with the basics of Azure Cloud.
Data masking is the process of hiding original data with modified figures. The main use of data masking is to protect classified or sensisitve data.
Data encyption is a security method that translates data into another form or code so that only people with access to the decryption key or password can access and read the data. Data encryption is primarily used to protect digital data from malicious or negligent parties.
Endpoint security is the practice of securing endpoints or entry points of end-user devices such as a desktop, laptop, or mobile device from being exploited by malicious attacks.
About the author
Tapan has over a decade of work experience in Business Intelligence, Product Management and Cloud Architecture and has excellent command over languages like Python, Go and Scala. He has worked extensively in Data Analytics and with tools like Thoughtspot and Tableau. He has a deep interest in Quantum Computing and Quantum Mechanics leading him to work considerably on Quantum Computing libraries such as Qiskit and Cirq.