Course details

Data Ops 16: Securing Big Data Streams

Data Ops 16: Securing Big Data Streams


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

Examine the security risks related to modern data capture and processing methods such as streaming analytics, the techniques and tools employed to mitigate security risks, and best practices related to securing big data.



Expected Duration (hours)
1.0

Lesson Objectives

Data Ops 16: Securing Big Data Streams

  • understand the main security concerns related to big data
  • understand key security concerns related to streaming data
  • understand key security concerns related to NoSQL databases
  • understand key security risks associated with distributed processing frameworks
  • understand key concerns and flaws related to data mining and analytics
  • understand risks related to end-point devices such as devices on the Internet of Things
  • understand some of the key ways that big data security concerns are addressed
  • understand how data streams are secured
  • understand how to deploy a VPN using Azure to secure data in motion
  • understand how end-point devices are secured using validation and filtering
  • understand how to use encryption to secure data at rest
  • recognize how big data and streaming data are secured
  • Course Number:
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    Expertise Level
    Beginner