大数据测试实战班
（座位有限，订满为止）
Course Description:
The focus in this course is on the development, maintenance and evolution of applications dealing with large volumes of data (called “Big Data”) in software testing field and finding high pay Big Data QA jobs
The target audience for this tutorial is who all are willing to learn big data testing and wanted to make his/her career into big data testing. All the users who are working in the testing profession and willing to move into big data testing should take this course.
In this course, we shall focus on such topics as:
Software Quality assurance (QA) concepts
Data warehousing, ETL & Big Data concepts
Linux & Shell scripting for the big data QA
Querying Data using Hive
Essentials for Hadoop
Hadoop/Big Data testing
Phase 1： Software Quality assurance (QA) concepts and Essentials for Hadoop
Total: 24 hours
Session 1: Introduction to Software Testing and Testing Concepts
· Test Activities
· Test Tools
· Effective Test Documentation
· Chapter Summary
Session 2: Software development methodologies, Test Cases and Scenarios
· Waterfall development methodology
· Agile development methodology
· DevOps deployment methodology
· Test Cases and Scenarios Fundamentals
· Test Cases Decision Tables
· Test Cases Equivalence Classes
Session 3: Unit Testing, Integration testing, System Testing, User Acceptance Testing
· Unit testing concepts
· Stubs and drivers
· Completion criteria
· Integration testing concepts
· Integration Faults
· Integration-testing methodologies
· System Test Concepts
· System Test Scenarios
· Performance Testing
· Examples
· Alpha and Beta Testing
· User Acceptance Test Concepts
· Preparation, Execution, Analysis
· Accepting Third-party Software
· Test Activities
· Test Tools
· Effective Test Documentation
· Chapter Summary
Session 4: Maintenance and Regression Test Testing
· Maintenance and Regression Test Concepts
· Testing in Corrective Maintenance
· Testing in Perfective Maintenance
· Testing in Adaptive Maintenance
· Selecting Regression Tests
Session 5: Essentials for Hadoop/Big Data testing
· Big Data Testing Strategy
· Testing Steps in verifying Big Data Applications
· Big Data Testing Test Activities
· Big Data Testing Test Tools
Session 6: Introduction to Big Data testing and use cases
· Roles and responsibilities of Big Data tester
· Key Challenges in Testing Big Data
· Test Plan and Test Cases
· Big Data Testing Techniques
Phase 2： Big Data Quality assurance (QA) skills and projects
Total: 24 hours
Session 1: Hadoop ETL & Big Data concepts
· What is ETL?
· What is Big Data?
· What is Hadoop?
· Hadoop components – HDFS, MapReduce & Yarn
· Introduction to HDFS & MapReduce
· HDFS Architecture
· HDFS Commands
Session 2: Linux & Shell scripting in big data testing
· Linux File & Directory commands
· Filter commands
· File Compare commands
· File Access Permissions
· Miscellaneous commands
Session 3: Querying Data using Hive
· Hive Overview
· Hive Characteristics and Features
· Hive Partitions & Buckets
· Hive Queries: Order By, Group By, Distribute By and Cluster By clauses
· Hive Aggregation Functions
· Hive Joins
· Working with Hue
Session 4: Project hand-on
· Uploading The Initial Data to HDFS
· Data Staging Validation
· Data Quality Check
Session 5: Project hand-on
· Output Validation
· Validation of structured and unstructured data
·
Session 6: Review all courses and interview questions
· Big Data Tester Daily Jobs
· Software Testing Interview questions and answers
【授课老师】Blair
多伦多软件测试课程创始人，就职于多家行业顶尖金融 IT 和政府机构（Manulife, CIBC,TD,IBM）10多年大数据测试技术大牛精心研发，多年上百例成功经验，三各月助你完全脱变，成功转型大数据测试，获取高薪稳定的计算机工作. 老师低调负责讲课精细深入，技术大咖，精通面试就业辅导，历经百余学员辅导，擅长沟通技巧，心态辅导，莫老师始终认为，没有找不到工作的学员，只有不会辅导的老师。遇到维多利亚，就是你最好的成长。十余年工作经验，亲和认真负责，对待学员像兄弟姐妹一样，总是鼓励学员去奋斗。
