Data science is all about trying to create a process that allows you to chart out new ways of thinking about problems that are novel, or trying to use the existing data in a creative atmosphere with a pragmatic approach.

Businesses are struggling to grapple with the phenomenal information explosion. Conventional database systems and business intelligence applications have given way to horizontal databases, columnar designs and cloud-enabled schemas powered by sharing techniques.

Particularly, the role of QA is very challenging in this context, as this is still in a nascent stage. Testing Big Data applications requires a specific mindset, skillset and deep understanding of the technologies and pragmatic approaches to data science. Big Data from a tester's perspective is an interesting aspect. Understanding the evolution of Big Data, What is Big Data meant for; Why Test Big Applications is fundamentally important.

Logix Guru’s Big Data & data analytics Testing Solution include:

Data Integration Testing
Source System Extraction Completeness & Correctness
Data Quality (Both Business and Technical) Completeness and Correctness
Transformations Completeness & Correctness
Subject Area Load Completeness & Correctness
Data Repository Testing
Subject Area Load Completeness and Correctness
Referential Integrity
Analytic Layer Testing
Correctness: Each Analytic Report/Adhoc Environments shouldbe Tested
Look and Fell of the information
Drill-Path Verification
Regression Testing requires particular focus on Enhancement and Maintenance Efforts.

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