At Qubiq Analytics, we deliver robust data engineering solutions that form the backbone of your analytics, AI, and business intelligence initiatives. Our expert team designs and implements modern data architectures that ensure your data is accurate, accessible, and ready for action—regardless of volume or velocity.
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We design cloud-native, hybrid, and on-premise data platforms tailored to your business needs. From data lakes to data warehouses and lakehouses, our solutions ensure scalable and efficient storage and processing.
We build secure, automated, and real-time data pipelines using tools like Apache Spark, Apache NiFi, Kafka, Airflow, and cloud-native services (AWS Glue, Azure Data Factory, etc.) to ingest, process, and distribute data across systems.
We create reusable and scalable ETL/ELT processes to extract, transform, and load structured and unstructured data, enabling downstream analytics and reporting at scale.
Seamlessly integrate data from diverse sources—databases, APIs, flat files, SaaS platforms, and IoT devices—to create a unified view of your business.
We implement metadata-driven frameworks and data catalogs that improve data discovery, governance, and lineage tracking.
Ensure clean, consistent, and trustworthy data with automated validation rules, anomaly detection, and cleansing mechanisms.
Build event-driven architectures and real-time data processing solutions to power analytics that react to events as they happen.
Leverage DevOps and DataOps best practices to automate deployment, scaling, and monitoring of data infrastructure using tools like Terraform, Ansible, and Kubernetes.
