Achieve more with automated Big Data testing.
With the rapid evolution of Big Data come challenges like bad data that can result in huge revenue loss. Our experienced quality engineers guarantee your data quality through extensive and automated Big Data testing.
Testing Big Data is a big responsibility.
Big data involves enormous volumes of structured as well as unstructured data, which require rigorous testing. Our skilled QA engineers ensure the quality of your data as well as the reliability of your big data processing and test data management, with effective functional and non-functional testing.
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Get precision testing done for data of every volume, variety and velocity.
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Leverage open-source testing tools by industry leading providers.
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Ensure successful data migration from source systems to Hadoop.
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Achieve superior data quality through expanded test capacity.
Get impeccable data quality.
You can rely on our detailed Big Data testing strategies to ensure you don’t have to compromise on business-critical processes due to system errors arising from massive data and multiple processing methods.
Strategically customize your data, to identify errors in the system and the cause and location of the error, because every data pipeline includes varied data sources, transformation and migration tools and processes and visualization tools.
Analyze assess and effectively test your data with our data analysts and QA engineers specialized in varied query languages (Python, R, Julia, NoSQL, SAS, Scala etc.) and trusted tools (Postman, QuerySurge, MapReduce or HIVEQL).
Improve your test coverage and mitigate all possible risks with our end to end testing approach, right from integration to visualization and deployment.
By leveraging our outstanding testing strategies and holistic approach, you can ensure that the consistency of your data in the data pipeline is secured.
Your one-stop-shop for zero-error testing.
We go beyond functional testing to incorporate automation, AI and usability. Our Big Data testing solutions eliminate risks through end-to-end testing of all the data sources and integrators to assure scalability and improved accuracy.
Be it API integration or direct JDBC connection, we customize automation according to your system requirements and format the data under processing for all integration points in a pipeline.
We constantly assess and monitor to achieve complete data validation, with thorough analysis of source and destination systems, testing of aggregate data counts, sampling and data sets, pre- and post-migration.
We perform ETL testing to validate your data quality and report testing to ensure the correct display of data indicators.
With built-in dynamic analysis, we put additional emphasis on the analytic platform (BI) results, which are more complicated due to the varied nature of the data input and loose structure.
We monitor database performance and test data syncs efficiency to ensure job completion time, memory utilization and data throughput. We’re ready with data expertise and synthetic data.
Scaling down for Big Data testing is not as simple as it is for traditional database testing. So, we solve your additional environmental requirements for Big Data testing, saving you the risk of the need to scale down.
We follow a collaborative approach with development teams to make our testing process effective, as operating the testing tools require specialist skills.
How can we help?
What business initiatives are you planning? It’s almost a given we have direct experience. What technologies are you currently using? We’re tool- and tech-agnostic and can integrate with anything you have. How would you like to engage with us? We have flexible models to suit your needs. Check out everything Qualitest has to offer.
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