Big data testing
Big data testing is the process of verifying and validating the functionalities in big data applications. Big data with variety, veracity, velocity, volume and value into various domains such as insurance, banking, mutual fund, security. Good expertise in domain and technology helps in doing the functional validation with application having huge data.
Traditional computing techniques do not fit for the large datasets collections as part of big data. Testing of these datasets involve various tools, techniques, and frameworks to process. Creation, storage and retrieval and analysis of large dataset collections as part of big data testing are remarkable as the volume, variety and velocity is much more.
Big data testing strategy
• Testing big data application is more verification of its data processing rather than testing the individual features of the software product.
• In big data testing strategy, QA engineers verify the successful processing of terabytes of data using commodity cluster and other supportive components.
• It demands a high level of processing speed & better testing skills.
Three types of processing:
• Batch.
• Real time.
• Interactive.
• Checking various characteristics like conformity, accuracy, duplication, consistency, validity, data completeness is involved in this process.
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