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AI-based Predictive Analytics for Automated Big Data Testing Services

Data migration testing using open source Big Data testing tools

Big Data Testing for building Secure, Scalable and cost-effective search apps

The speed and efficiency of Enterprise search systems to skim and sort through gargantuan cloud library make them highly valuable. A global Enterprise search solutions provider wanted to perform big data testing and achieve faster time-to-market.

Read how Cigniti overcame the challenge of complex test data management and spearheaded reduction of 15% test cycle time and 20% costs.

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Big Data Automation Testing - Needs & Challenges

Testing Big Data applications requires a scientific temperament, analytical skills, and deep and practical understanding of data science. Following are a few needs and challenges that make automated Big Data testing a must.

  • Increasing need for live integration of information: Enterprises need to have constantly clean and reliable data. This can only be ensured through end-to-end testing of the data sources and integrators.
  • Instant data collection & deployment: Simply deploying the data isn’t enough. Enterprises need AI-based predictive data analytics testing to effectively take Decisive Actions by analysing the insights from the minute patterns in large data sets. Unless the apps & data feeds are tested & certified for live deployment, correct decisions cannot be made.
  • Migrating legacy to new systems: While migrating data from legacy systems, there are high chances of disruption/downtime, data integration challenges, and loss of data. Data Migration Testing helps verify all functional & non-functional aspects of the app post-migration.
  • Real-time scalability challenges: Big Data apps need to match the level of scalability & data processing involved in a given scenario. Any error in the architectural elements of Big Data apps can lead to severe business impact. Software testing involving smarter data sampling, cataloging techniques, & high-end big data performance testing capabilities are thus critical to meet the scalability problems of Big Data apps.

Cigniti’s comprehensive Big Data automation testing helps automate repeatable activities & includes the following offerings.

Increasing need for live integration of information

  • Evaluate the reporting app for end-user’s adaptability
  • Review the observations with user & dev group

System & Integration Testing

  • API testing & validation of business rules
  • End-to-end system testing from sources to target
  • Validate outbound interfaces & downstream data

Requirements Ambiguity Testing

  • Identify ambiguities (Words, Phrases & Logic) from business requirements
  • Create Requirements Ambiguity Report & review with business & development teams

Data Quality & Extract, Transform, Load (ETL) Testing

  • Data model, Meta data, data types, formats, Field mapping, Referential integrities (-checking if all data references are valid), & Surrogate keys (-unique identifiers)
  • ETL logic, Error logic and boundary conditions

DW Dashboards/Reports Testing

  • Hierarchies, Rollups (summarized datapoints), navigation, drill downs
  • Security (user/roles authentication, data security)
  • Alerts, notifications (Emails, Smart Devices etc.)
  • Support end user business process validation & test case execution & defect analysis

Big data Performance & Stress Testing

  • Performance testing of the DW & BI Apps
  • Stress test of the application with peak workload
  • Test the Reports response time as per SLAs

AMZ Big Data Automation Testing Offerings & Value Add

Deliver value faster with Augmented Analytics

Deliver value faster with Augmented Analytics

Multi-iteration testing methodology for leading bio-pharmaceutical company

Technology & Tools Expertise

A Digital-First Journey Anchored in Quality-First Principles

Data Integration - Drawing Large & Disparate Data Sets Together in Real-Time

Current data integration platforms which have been built for an older generation of data challenges, limit IT’s ability to support the business. In order to keep up, enterprises need to look at next-generation data integration techniques & platforms such as API testing & validation of business rules, outbound interfaces & downstream data.

They need to perform end-to-end system testing & integration testing, and develop the ability to understand, analyze and create test sets that encompass multiple data sets. This is vital to ensure comprehensive Big Data testing, data analytics testing, visualization testing, and data migration testing.

 

Cigniti leverages its experience of having tested large scale data warehousing and business intelligence applications to offer a host of Big Data testing services and solutions such as BI application Usability Testing. Cigniti’s open source big data testing tools help evaluate the reporting app for end-user’s adaptability and continuously review the observations with user & dev group, as a part of our Agile and DevOps testing.

Testing Data Intensive Applications & Business Intelligence Solutions

Testing New Age Big Data Applications –Cigniti Testlets

Cigniti Testlets offer point solutions for all the problems that a new age Big Data application would have to be go through before being certified with QA levels that match industry standards.

Cigniti has developed proprietary Testlets for:

  • Consumer Partitioning testing
  • Social Indexing testing
  • Data Mutation testing
  • Testing in Production testing
  • Performance testing
  • Security testing

50+

Hadoop certified test professionals

200+

test professionals with expertise in data analytics and data quality testing

Big Data Testing Expertise & Framework

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