AI-based Predictive Analytics for Automated Big Data Testing Services
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 Big Data Automation Testing Offerings & Value Add
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
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.
Testing Data Intensive Applications & Business Intelligence Solutions
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.
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.
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
Big Data Testing Expertise & Framework
Hadoop certified test professionals
test professionals with expertise in data analytics and data quality testing
Big Data Testing Framework
Cigniti’s big data testing framework provides the following benefits:
- Raw data analysis (structured & unstructured)
- Validation of data load frequency, Query processing, scheduling of jobs, load dependency checks
- ETL validations
- Metadata layer testing
- Test data creation and verification
- High-volume and high-scale tests
- Performance and failover tests
- Cloud testing for the data warehouses
- Reliability testing
- Testing statistical, time series and probabilistic analysis
- Validate AI-based predictive data models
- Mapping of every field in the report with the schema and Source System values
- Layout format, style sheets, prompts and filters attributes and metrics on the report
- Drilling, sorting and export functions of the reports in the Web environment
Features of Cigniti’s Database Test Automation Framework
Cigniti’s database test automation framework:
- Enables creation of reusable scripts on the source & target databases for the critical data elements
- Cigniti’s database test automation framework:
- Customized testing tools (using Excel macros, VB scripts, Java scripts, Unix scripts) for the data validations
- Use/build automated tools to compare pre-migration & post-migration data sets
- Supports development of reusable automation test scripts based on functional requirements
Automated ETL Testing with Informatica/SSIS Package:
- Extract Data from Source
- Transform data using Informatics Transformation
- Load the data in Destinatio
- Verify the destination data
Technology & Tools Expertise
Consult our experienced team of experts for overcoming your challenges related to big data testing, data migration testing, data analytics testing, and big data performance testing.