Designing Batch Processing and Data Security


Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number
Expertise Level


Overview/Description
Big data analytics with Microsoft Azure requires effective deployment of various frameworks and technologies. This course covers batch processing technologies and data security tools in Azure, and prepares you for exam 70-475.

Target Audience
Professionals who are preparing to take the 70-475: Designing and Implementing Big Data Analytics Solutions certification exam, and who are experienced in designing, programming, implementing, automating, and monitoring Microsoft Azure cloud platform solutions. Exam candidates should also be adept at using development tools, techniques, and design methodologies associated with the implementations of cloud-based big data analytics solutions.

Prerequisites
None

Expected Duration (hours)
2.0

Lesson Objectives

Designing Batch Processing and Data Security

  • start the course
  • recognize key features of Apache Sqoop
  • demonstrate how to import data from an RDBMS to the Hadoop Distributed File System
  • manage and monitor clusters with Apache Ambari
  • manage workflows with Oozie
  • use HCatalog for table and storage management in Hadoop
  • recognize the key functions of Apache Zookeeper
  • use Apache Pig for data analysis
  • manage large datasets with Apache Hive
  • recognize key features and functionalities of Azure Batch
  • recognize key features and functionalities of Apache Mahout
  • identify key features and data sources of Spark SQL
  • use MapReduce for writing applications
  • use PowerShell to handle big data
  • use SQL Server Analysis Services
  • process large datasets with Data Factory and Batch
  • recognize Azure's technical data security capabilities
  • features of role-based and row-based security
  • configure firewall and proxy server settings
  • recognize key functions of Shared Access Signatures
  • recognize key features and capabilities of batch processing technologies

    • Course Number:
    df_dibd_a02_it_enus

    Expertise Level
    Intermediate