Programmatic delivers end-to-end big data expertise from architecture to AI integration. With multi-cloud mastery, automated pipelines, and outcome-focused delivery, we build intelligent, scalable platforms that turn data into measurable business value.
Big Data Services
Process, Analyze & Monetize Massive Data at Scale
We help enterprises collect, manage and analyze large data volumes in real time.
Our big data frameworks unlock insights, reduce latency and power predictive analytics.
- Scale your data potential with AI-driven big data solutions.
Big Data Services Solutions
Programmatic Big Data Service Features
As data grows exponentially, legacy architectures and siloed systems can’t keep up.
Big data initiatives fail when they lack the right architecture, integration, or governance strategy.
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Our Big Data Service Offerings
We build end-to-end big data platforms using Apache Spark, Databricks, Kafka, and Hadoop — architected for high availability, scalability, and performance.
Our solutions are cloud-agnostic and support batch, streaming, and real-time workloads seamlessly.
Enterprise-grade platforms. AI-ready by design.
We engineer automated data pipelines that continuously move and transform massive datasets across systems and clouds.
Using Airflow, Glue, NiFi, and dbt, we deliver resilient data flow frameworks with error handling, logging, and recovery built in.
Capture and act on events as they happen with Kafka, Flink, and Spark Streaming.
We help you process IoT, sensor, log, and clickstream data to power use cases like predictive maintenance, fraud detection, and real-time personalization.
Programmatic bridges the best of both worlds: the flexibility of data lakes and the performance of data warehouses.
We design data lakehouse architectures that unify storage, analytics, and governance enabling seamless access for BI, ML, and LLM workloads.
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How Data Analytics Services
Benefit Your Industry
2026 Guide to Data Services (Scaling Big Data for AI)
As big data meets AI, scalability and real-time orchestration define the new frontier.
Highlights:
- Managing petabyte scale streaming and batch pipelines
- Leveraging Spark, Kafka, and Databricks for intelligence
- Integrating predictive analytics into big data frameworks
- Optimizing compute and storage for cost efficiency
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Get in touch.
Have a data challenge, a brilliant idea, or just curious about what we can build together? We’re ready to listen and collaborate.
Frequently Asked Questions
Big data refers to large, fast-moving, and diverse datasets that traditional databases can’t handle effectively requiring distributed systems like Spark or Data bricks.
We design streaming architectures using Kafka, Flink, and Spark Streaming, supported by cloud-native scaling and observability.
A data lake stores raw data, while a big data platform processes, analyzes, and operationalizes it for analytics and AI.
Yes we migrate and modernize Hadoop workloads into server less, cloud-native data lake houses with zero disruption.