Move from unstructured to structured and from data to intelligence.
Big Data systems are critical for today’s business environment. The process must accommodate testing during various data processing stages like data creation, storage, retrieval, and analysis. Expert database skills and automation skills are required to manage the volumes and varieties of data. Testing challenges: No user interface, huge volume of data, variety of sources, bad or missing data
Large volumes of data from various sources are tested using clustering methods. We help you process data systematically, real-time or in batches. Data quality is tested for accuracy, duplication, validity, consistency, etc.
Extract the right data from right sources and ensure it is compatible with the target systems. Achieve corporate data governance with centralized data life cycle management, compliance and audit and database replication and archival.
Verify the business logic at multiple times to make sure data segregation and aggregation rules are correctly applied. To unlock the full potential of big data, enterprises need to implement the right strategies improve test quality and identify defects at early stages.
Check for the data integrity to make sure data is loaded successfully into the target system and also check for data corruption if any. Qapitol QA supports enterprises with strategies to test large datasets using modern tools and frameworks.