Big Data Processing & Pipelines

Transform Data into Actionable Insights with Scalable Big Data Pipelines

Efficient Big Data Processing

Universe Eswan builds robust big data pipelines to ingest, process, and analyze massive datasets. Our solutions ensure high performance, scalability, and real-time insights to help businesses make data-driven decisions effectively.

Step 1: Data Assessment

Identify data sources, volume, velocity, variety, and quality requirements.

Step 2: Architecture Design

Design scalable data pipelines and storage solutions for batch and real-time processing.

Step 3: Data Ingestion

Use ETL/ELT processes to ingest data from multiple sources into a centralized system.

Step 4: Data Processing

Process data using frameworks like Apache Spark, Hadoop, or Flink for analytics and machine learning.

Step 5: Data Storage

Store processed data in scalable storage systems like HDFS, AWS S3, or NoSQL databases.

Step 6: Analytics & Reporting

Generate dashboards, reports, and predictive insights for business intelligence.

Step 7: Monitoring & Optimization

Continuously monitor pipeline performance, optimize processes, and ensure data quality.

Technologies We Use

Apache Spark / Hadoop
Kafka / RabbitMQ
AWS S3 / Azure Data Lake / GCP
NoSQL: MongoDB, Cassandra
ETL / ELT Tools
Airflow / NiFi
Python / Java / Scala
Tableau / Power BI / Looker

Why Choose Universe Eswan?

Scalable Pipelines

Handle large volumes of data with high reliability and minimal latency.

Real-Time Insights

Enable businesses to make timely, data-driven decisions.

Optimized Performance

Efficient data processing ensures cost-effective operations and faster results.

End-to-End Data Management

From ingestion to analytics, we provide a complete big data solution.