Big Data Testing Services

Infosys Big Data and Analytics Testing services ensure 100% validation of all structured and unstructured data with focus on achieving superior data quality. Our end-to-end testing methodology addresses all Big Data testing requirements including testing metrics definition, tooling, and test data needs. Our offering helps accelerate time-to-market, reduce total cost of quality and guarantees 100% data validation.

With the Infosys Big Data Testing solution, leveraging machine learning based validation techniques for predictive analytics, you can reduce costs by up to 30% and time-to-market by up to 20%.

Infosys Big Data and analytics testing services are powered by

Proven accelerators such as Infosys Data Testing Workbench, Analytics Validation Platform and BI Tester 3.0
Infosys 4D++ Testing Framework for addressing functional and non-functional Big Data testing needs
Extensive reusable assets including the process repository, re-usable strategies and tools
CoE-driven Big Data skill builder, lab for research and development of frameworks and utilities, continuous training and expert-competence enablement

Offerings

The comprehensive Infosys Big Data and Analytics Testing service helps companies with

Data Ingestion Testing: Structured, unstructured and semi-structured data sources
Testing Migration to Big Data Lakes:Structured to NoSQL data sources
Analytics Testing:Predictive models
Visualization Testing:Data insights
Data Quality in Big Data:Acquire, cleanse and integrate data

Solutions

Infosys Data Testing Workbench

An Infosys innovation which helps to validate data ingestion to Big Data systems, migration to Data Lake, and data quality, saving up to 40 percent of test execution effort

Infosys Big Data Analytics Validation platform

For automated validation of predictive analytics in cloud

Data Quality Analyzer Framework

For Big Data platforms providing 100 percent accuracy for business rules validation

Infosys 4D++ Test Approach

Covers all possible methods of Big Data testing while addressing functional and non-functional Big Data testing requirements. Provides 35% reduction in effort and 100% data coverage for testing