Overview

In a world of digital transformation, we are beginning to see that data and analytics are changing the way organizations operate. Collecting data in operational systems and then relying on nightly batch extract, transform, load (ETL) processes to analyze the data is no longer sufficient.

At CIGNEX Datamatics, we help enterprises to build Big Data and IoT applications using Apache Kafka for real-time data streaming and analysis. CIGNEX Datamatics has partnered with Confluent, the company founded by the creators of Apache™ Kafka, to help enterprises solve the challenges of data integration by building stream processing applications with Kafka.

Our experienced Big Data experts roll-out wide range of big data use cases such as customer 360 degree view, social listening and engagement, risk and fraud detection, internet of things, predictive analytics and more.

Why Apache Kafka?

Apache Kafka is a fast, scalable, fault-tolerant messaging platform for distributed data streaming. It is used for building real-time data pipelines by streaming social data, geospatial data or sensor data from various devices. It lets you...

  • Publish and subscribe to streams of data like a messaging system
  • Store streams of data in a distributed, replicated cluster
  • Process streams of data in real-time.

Kafka is horizontally scalable, fault-tolerant, wicked fast, and runs in production in thousands of companies.

Services

Kafka
Consulting

Our experienced Kafka consultants help enterprises to build real-world Big Data applications that integrate and analyze high velocity data sources.


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Kafka
Integration

Our Apache Kafka experts can solve enterprise's data streaming and processing challenges – processing and delivering streams of data efficiently and in real time.


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Kafka
Implementation

Our Big Data consultants can integrate Kafka to support your Big Data use case.


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Solutions

With Kafka and based on Confluent, our Kafka experts have created solutions for Stream Processing , Website Activity Tracking, Metrics Collection and Monitoring, Log Aggregation and Event Sourcing.

Log Aggregation Framework - Monitor & Detect Failures Ahead of Time

We have created a secure centralized Log Processing Framework based on ELK stack with powerful visualization and search functionalities enabling high availability through

  • Real time monitoring of core micro services
  • Real time access to failures leading to faster turnaround time
  • Integrated framework to analyze failures/errors from diverse applications through a single interface


Log Aggrgation

Event Driven Architecture - Building real-time streaming applications, streaming data pipelines, and event-driven architectures

We have created event-driven architecture using Kafka,that can change over time as different processors may react to events, which can be reprocessed while the data model evolves simultaneously. Applications built using this architecture can help in

  • Website & Network monitoring
  • Fraud detection
  • Web clicks
  • Advertising
  • Creating Internet of Things

Event Driven

Why CIGNEX Datamatics ?

  • 10+ Enterprise Big Data Implementations / Deployments
  • 110+ Big Data Analytics team