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How big data development knowledge will help big data testing. What are the requirements for BIG data testing. Does ETL testing cover big data?

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Hello Ashok, You will first need to understand the fundamentals of hadoop and some linux commands. For testing map reduce jobs,you will have to understand flow of map and reduce and then verifying by output of programs that the system is working correctly. You may also need creating large number...
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Hello Ashok, You will first need to understand the fundamentals of hadoop and some linux commands. For testing map reduce jobs,you will have to understand flow of map and reduce and then verifying by output of programs that the system is working correctly. You may also need creating large number of data for testing real time scenarios. read less
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understanding BigData environment is very much needed for Big Data Testing. ETL testing will help you on Big Data Testing
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One can be successful in Bigdata Testing if having a good understanding on the Big data Basics and Good Understanding on the Hadoop Ecosystem and the components belonging to Big Data. The ETL testing will be an advantage in Bigdata as here also you are dealing with Data and where ETL is required....
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One can be successful in Bigdata Testing if having a good understanding on the Big data Basics and Good Understanding on the Hadoop Ecosystem and the components belonging to Big Data. The ETL testing will be an advantage in Bigdata as here also you are dealing with Data and where ETL is required. But that alone will not serve the purpose read less
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ETL Testing is entirely different BIG DATA Testing are Random Sample and Sample Error (sd/sqrt(sample size) and difference statistical parametric and nonparticipants tests are required for analysis
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Big data overview knowledge helps in big data testing. ETL testing does not cover big data
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ETL testing won't be sufficient enough to cover big data testing.In Big Data testing there are various components need to be tested e.g 1. Hadoop File System need to be tested 2. Transformations need to be tested 3. workflow needs to be tested If the project is mostly implemented in PIG and HIVE...
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ETL testing won't be sufficient enough to cover big data testing.In Big Data testing there are various components need to be tested e.g 1. Hadoop File System need to be tested 2. Transformations need to be tested 3. workflow needs to be tested If the project is mostly implemented in PIG and HIVE , then ETL kind of testing will be ok. But if the project is implemented in mapreduce/spark then additional testing need to be done. The cluster testing is also key to know status of all the nodes . read less
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Big Data Hadoop Training Java

To do BigData Testing, currently there are no frameworks in the market, if they are launching also currently none of the IT Company is using, better you have an idea about BigData Developer, then you can think about testing area.
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Hadoop big data expert and Siebel consultant

Hi, To be successful, Big Data testers have to learn the components of the Big Data ecosystem from scratch. Since the market has created fully automated testing tools for Big Data validation, the tester has no other option but to acquire the same skill set as the Big Data developer in the context...
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Hi, To be successful, Big Data testers have to learn the components of the Big Data ecosystem from scratch. Since the market has created fully automated testing tools for Big Data validation, the tester has no other option but to acquire the same skill set as the Big Data developer in the context of leveraging the Big Data technologies like Hadoop. This requires a tremendous mindset shift for both the testers as well as testing units within organizations. In order to be competitive, companies should invest in Big Data-specific training needs and developing the automation solutions for Big Data validation. Thanks Sravanthi read less
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Hi, we will help you,
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