Big data is a collection of large datasets that cannot be processed using traditional computing techniques. Testing of these datasets involves various tools, techniques and frameworks to process. Our testing expertise: Here is the high-level overview of phases in Testing Big Data Applications by InfoStride team.

Phase 1: Data Staging Validation

The first step of big data testing also referred as pre-Hadoop stage involves process validation. Data from various source like RDBMS, weblogs, social media, etc. should be validated to make sure that correct data is pulled into system

Phase 2: MapReduce Validation

The second step is a validation of "MapReduce". In this stage, the tester verifies the business logic validation on every node and then validating them after running against multiple nodes, ensuring that the Map Reduce process works correctly.

Phase 3: Output Validation Phase

The final or third stage of Big Data testing is the output validation process. The output data files are generated and ready to be moved to an EDW (Enterprise Data Warehouse) or any other system based on the requirement.