Big Data Testing

Managing and validating large-scale data systems requires specialized testing strategies—and that’s where we excel. With strong expertise in Big Data ecosystems, our QA team ensures the accuracy, reliability, and security of data across complex platforms and pipelines.

We test not just the volume, but the veracity and integrity of your data throughout its lifecycle.

Our Big Data Testing Focus Areas:

01. Data Quality & Validation

We validate massive datasets to ensure completeness, accuracy, consistency, and timeliness—no matter the volume or source.

02. Data Ingestion & Transformation

We verify that data is correctly ingested from various sources and accurately transformed through ETL (Extract, Transform, Load) processes.

03. Workflow & Pipeline Validation

Our team tests scheduled jobs, data pipelines, and workflow orchestration tools (like Apache NiFi, Airflow, or Spark) to ensure smooth, uninterrupted processing.

04. Role-Based Access Controls

We ensure sensitive data is protected by validating access control policies and user permissions across distributed systems

05. End-to-End Data Integrity

From ingestion to analytics, we maintain data integrity across platforms like Hadoop, Hive, Kafka, and cloud data lakes (AWS, Azure, GCP).

Data Quality & Validation
Data Ingestion & Transformation
Workflow & Pipeline Validation
Role-Based Access Controls
End-to-End Data Integrity

Tools & Frameworks We Work With:

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