Big Data
Testing

Move from unstructured to structured and from data to intelligence.

Qapitol QA > Big Data Testing

Unlock the full
potential of Big Data

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

Get the data
quality  you desire

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.

Data &
Extraction Validation

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.

Business Logic Data
Validation by Transformation

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.

Output
Validation & Data Loading

unified testing framework

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.

Big data is high-volume, high-velocity, and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.”

Gartner

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