Bigdata Testing Training 2019-08-09T17:39:42+05:30

Bigdata Testing Training

  • 40 Days Online Training
  • 40+ Days Classroom Training
  • Free Unlimited lab Access

Testing Big data applications involves, testing of the various data storage tools, framework and processes.  Big data testing focuses on performance and functional testing validating the data processing functions of the application framework.

Online Training

Rs. 8,999 *45 days access


Classroom Training

Rs. 6,999 *45 days access

100% Placement Assistance
  • Best Discounts
  • Expert Educators
  • Flexible Schedule
  • 24x7 Tech Support
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Training Features

Top Industry Trainers

All our trainers are real-time industry experts. Quality of training is our primary motto and we ensure each and every program of ours are delivered by the best trainers.

Industry Relevant Curriculum

Course designed keeping in mind the present and future needs of the Industry. All our training programs are constantly updated and tuned to meet Industry requirements.

Real-Time Case Studies

Real-Time case studies and project are mandatory part of our training programs. All the assignments are designed to help students understand practical applications of the learning’s.

Flexible Schedule

With options to join classroom and online batches, you have a wide array of options in terms of batches, timing and duration allowing to you plan your learning, and achieve your carrier goals.

Feedback Management

Continuous feedback and interaction with our student community help us identify concern area and mitigate issue early on ensuring a great learning environment.

State-of-art Lab Infrastructure

Best in class Lab infrastructure to help students work on the latest assignments and project. Practical application of the learning ensures a more satisfied training.

Description

Big data is large collection dataset which is not processed using the traditional computing methods. Big data applications focus on processing large dataset, storage and generation of analytical reports. Testing of such Big data applications involves, testing of the various data storage tools, framework and processes. Big data testing focuses on performance and functional testing validating the data processing functions of the application framework.
Quality Thought offers the best Big Data Testing program with emphasis on real-time application testing case studies. Our course curriculum has been prepared by trainers with real-time industry experience with a lot of emphasis on real-time case studies and assignments. The primary objective of the Big Data Testing is to help students and working professionals learn and master all the important facets of Big Data testing ensuring the students are market ready for can grab opportunities across industry domain.
The program focuses on Big data and Hadoop concepts. It highlights the need for understanding the processes involved managing large data volumes, processing application working on large scale data etc.

UNIX commands and processes are discussed in order for the students to master the skills needed to manage operating system and application frameworks.

Hadoop testing concepts are mastered with the focus on Test plans, estimates, test cases, test scripts, defect tracking and reporting etc. These topics will help student up skill and be a effective QA testing professional on the Hadoop platform.

Big Data Testing program can be picked up by anyone good hands on with Manual Testing and understanding of elementary programming and Bid data processing applications like Hadoop. The course is applicable to:

Graduates/Post Graduates/Fresher
Working IT professional from programming, web development and DBA fields
Software programmers
Manual Testers

Testing is one of the key activities associated with any project development life cycle. Proper testing is of at most importance in application product development. Testing engineer will always be in demand and are the backbone of software product development companies. With the increase in the usage of Big Data applications across industry for various analytical reporting and other data crunching applications the need for QA engineers with expertise on Big data testing has been on a rise. Test engineers and Student with the right skill set and a flare for testing have great opportunities in the Testing space and a Career is testing technology will be excellent and fulfilling.
Big Data Testing is for people for any background and prior experience in Manual Testing. People from non-programming background with a flair for understanding programming and Data management can also get into this program and learn all the concept of testing including manual testing before picking up with Big Data testing.

Bigdata Testing Course Curriculum

Duration: 45 Hours

  • What is Big Data?
  • 3 V’s Concepts
  • Diff Problems and Solutions of Big data

  • What is Big Data?
  • What is Hadoop and History of Hadoop?
  • Hadoop Architecture
  • Hadoop ecosystem components
  • Hadoop Storage: HDFS
  • Hadoop Processing: MapReduce Framework
  • Hadoop Server Roles: Name Node Secondary Name Node, and Data Node
  • Anatomy of File Write and Read.
  • Different Components of Hadoop.

  • Echo, cat, cp, cut, ls, Cd, touch
  • mkdir, rmdir, rm,
  • chmod, mv, head, tail
  • Date, PS, uniq, diff
  • grep,vi editor

  • Significance of HDFS in Hadoop
  • Features of HDFS
  • 5 Daemons of Hadoop
    • Name Node and its functionality
    • Data Node and its functionality
    • Resource Manager and its functionality
    • Node Manager and its functionality
    • Secondary Name Node and its functionality
    • Introduction about Blocks
    • Data Replication
    • Data storage in Data Nodes
    • Replication Configuration
    • Fail Over Mechanism
    • Replication Factor
    • Changing block size for file and Directory
  • File Processing in HDFS
    • How to process files in Edge node?
    • How to load files into HDFS?
    • File validation between Source and Target
    • Test cases preparation for File processing

  • Introduction to Apache PIG
  • MapReduce Vs Apache PIG
  • SQL Vs Apache PIG
  • Physical & Logical Layer
  • Different Data types in Apache PIG
  • Modes of Execution in Apache PIG
    • Local Mode, Map Reduce or Distributed Mode
  • Execution Mechanism
    • Grunt shell, Script, Embedded
  • Transformations in PIG
  • How to write a simple PIG Script
  • Hands on with PIG lactic script
  • Validation on PIG scripts
  • Test cases preparation for PIG scripts

  • HIVE Introduction
  • Hive Architecture and Installation
  • Comparison with Traditional Database
  • Operators and Functions
  • Hive Meta Store and Integration with MySQL
  • Hive integration with Hadoop
  • SQL vs. HIVE QL
  • Partitioning, Dynamic Partitioning and Bucketing
  • Hive Tables (Managed Tables and External Tables, Storage Formats, Importing Data, Altering Tables, Dropping Tables)
  • Hive data format – Text, ORC, Avro, parquet

  • Introduction to SQOOP
  • How to connect relational database using SQOOP
  • Different Sqoop Commands
    • Different flavors of imports, Export, HIVE imports
  • Hands on with Examples

  • Flume Introduction
  • Flume Architecture
  • Flume Master, Flume collector and Flume Agent

  • Oozie Introduction
  • Oozie Architecture
  • Oozie Configuration files
  • Oozie Job Submission
  • Workflow.xml
  • Coordinator.xml
  • Job. Coordinator. properties

  • Introduction to Spark
  • Spark Vs Map Reduce Processing
  • Architecture of Spark
  • Spark Shell Introduction
  • Creating Spark Context
  • File Operations in Spark Shell
  • Real time Examples of Spark
  • Spark Components
    • Spark Core
    • Spark SQL
    • Spark Streaming
    • Spark ML Lib

  • Importance of Hadoop Testing
  • Responsibilities of Hadoop Tester
  • Real time scenarios for Hadoop Tester
  • Different approaches for Hadoop Testing
  • How to validate data for multiple sources
  • Hot to prepare Hadoop Test Plan
  • How to prepare Estimates
  • How to design Test Cases
  • How to design Test Scenarios
  • How to prepare Test scripts
  • How to prepare Test data for test cases
  • How to execute Hadoop Test Cases
  • Defect Tracking and Reporting
  • Types of defect in Hadoop Testing
  • Challenges in Hadoop Testing

  • Project Name
  • Project Description
  • Client Name
  • Client Description
  • Business Background of Project
  • Process followed in the Project
  • Tools used in the Project
  • Environments in the Project
  • Team Size
  • Project Architecture
  • Testing Life Cycle in the Project
  • Query Tracker
  • Test Plan preparation
  • Test Cases preparation
  • Requirement Traceability Matrix
  • Review process in Project
  • Test case Execution
  • Defect Life Cycle in project
  • Role of Quality Centre in project
  • Regression Testing in Projec:
  • Bugs Identified in Project
  • Risks Identified in Project
  • Challenges identified in Project

  • Practical Sessions
  • Interview KIT
  • Resume Preparation
  • Mock Interviews
  • Support from Quality Thought to get the job and after got the job also

Certification

Quality Thought’s Bigdata Testing Certification Process:

  • Quality Thought will provide a certificate to the students who successfully completed their Bigdata Testing training. The certification will be provided within one week of the training completion.
  • The certification will be given to the students who have successfully completed their projects and assignments on time.

Frequently asked questions

Students can benefit from our State of the art lab infrastructure facilities at all our training centers across the city. Our lab facilities are available through the day on all working days. For our online students, they can connect to our servers and other lab facilities over the internet and practice. These facilities are available 24X7.
If the student misses out of attending any session, he or she can re-attend the session by:
1. Attending the same session in another batch if student is attending classroom based session.
2. For online sessions, recording of the classes can be accessed by the student at all time to help revisit and listen the sessions missed out.
All our trainer are real-time industry experts with minimum of 10+ years of experience. Complete profiles of our trainers are available for review at our center and students are free to come interact with them and know more about them, before enrolling for programs.
All training programs conducted by Quality Thought are available in 3 modes, instructor based classroom programs, instructor based live online training and self-paced video based training. Students can choose
All discounts are subject to case-to-case basis. Please feel free to meet our administration staff to have a better discussion on the same. We do offer a variety of discounts and concession to our students coming in from different backgrounds.

For all corporate training requirements please feel free to get in touch with our administration staff managing corporate marketing and interaction. We have of the finest programs and offer to corporate with best-in-class programs.

Bigdata Testing Training Reviews

The Big Data Testing program at Quality Thoughts is good, and I do recommend it all people interested in Big data testing. Nice institute with great attention to delivery.
Charan

Me and my friend recently attended Big data Testing at Quality Thoughts and the training was very good and informative. The placement assistance program is also good.
Deepali

I participate in the Big Data testing program with Quality Thought recently in the online classroom. The faculty was really great and helped us master the subject with ease.
Somaji

The placement assistance Quality Thought provided after my Big Data Testing programm helped me bag an excellent opportunity with a leading MNC. Thank you QT.
Monali

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