BIG DATA TESTING
Big data is a giant, fast-moving freight train of information that grows larger, faster, and more “freighted” by the day. DBMS systems (and RDBMS and ORDBMS) are like slow-moving cranes in rusty rail yards when it comes to accessing and processing information on the big data train. As a result, an industry has grown up around leveraging the power and momentum of big data. Pyramid brings a specialized set of testing tools and protocols to ensure the scalability, performance, continuous availability, and security of big data for your business. Our Big Data Testing Strategy is built to address the dynamic challenges of big data ecosystems, uncovering “bad data” while creating a testing infrastructure designed to test more data faster. Big data is a powerful resource that demands equally powerful expertise to make it work. Pyramid helps businesses take advantage of the increasingly valuable cargo on the Big Data Train.
Big data is a fast-growing marketplace that is driving demand for specialized products. These products, in turn, require specialized testing. Pyramid helps implement testing of massively scalable solutions for big data infrastructures. Our QA designers bring innovative new testing solutions to performance, security, and data quality that provide fast feedback within development iterations.
Pyramid Big Data Testing Solutions
Pyramid’s robust Big Data Testing Strategy (BTDS) is built to mitigate rapidly evolving data integrity challenges and ensure robust quality assurance processes for big data implementations. To address the dynamic changes in big data ecosystems, Pyramid helps organizations streamline their processes for data warehouse testing, performance testing, and test data management.
Pyramid Big Data Testing Approach
Pyramid’s collaborative data testing solution finds bad data and provides a holistic view of the “health” of a company’s data, ensuring that data extracted from sources remains intact at the target by analyzing and quickly pinpointing differences at every touch point.
- Big data warehouses are organized into smaller units that are easily testable, improving test coverage and optimizing big data test sets.
- QA Designers perform parallel testing in a distributed environment.
- Test data quality is strengthened by thorough planning, designing, and infrastructure setup process.
- Big data testing infrastructure requirements are assessed first, then the infrastructure is designed and implemented.
- QA Designer skills include white box testing and data analysis.
- More data is tested faster, using automated testing processes across various platforms.
- Best-in-class big data testing solutions and strategies deliver more business value.
- Pyramid brings deep testing experience across platforms, including Hadoop, MongoDB, Oracle, Teradata, IBM, Microsoft, HortonWorks, and all of the major vendors, along with flat files and XML.