Perceptive. Agile. Responsive

Big Data Analytics Solutions

Business enterprises are having a hard time grappling with the rising data volume and adding to their challenges are the complexities and the need to derive value out of their existing datasets. These new challenges present opportunities as well and this is where we assist our clients. Our multi-platform expertise and skills in big data analytics are designed for a fast-paced world where users have access to insightful data whenever they need it.

The analytics platforms that we implement are well suited for both structured as well as unstructured data, repeatable tasks that address flexibility and speed. They are also ideal for ad hoc data discovery, exploration and unstructured analytics. Our core capabilities include Hadoop-based analytics, stream computing, data management, use case identification along with application development and maintenance..


Generate and present a 360-degree view of your enterprise with big data and analytics solutions from Clavax. With an advanced data analytics platform and solutions, faster processing is now possible in real time for formulating more informed and smart decisions.
Our analytics solutions facilitate the following:

Stream Computing

Stream computing is about the continuous integration and analysis of data-in-motion to deliver high-performance real time analytics. This computing environment comprises a development environment along with high-speed runtime architecture. The major advantage of stream computing is that it allows organizations to detect risks and opportunities from high-velocity streams of incoming data that can only be acted upon at moment's notice. Such high-velocity data often originate from real time mediums like market data, sensors, mobile, Internet of Things, transactions and even clickstreams, which often remain un-navigated.

With the implementation of Stream Computing, organizations can:

  • Enhance existing data models with new insights
  • Preempt action on newly generated insights before opportunities are lost for forever
  • Analyze as well as act on rapidly changing data in real time
  • An option to shift from batch processing to real time data analytics and decision making processes

Data Management

Big Data management comprises two entities - one is the data itself and the other is data management - along with how the two function together to achieve business as well as technology goals. The application of big data tools, platforms and management disciplines is the basis for managing big data. There is a difference in terms of structure, content and the intended use of traditional and big data, with each category having multiple variations to it. To account for this diversity, technology solutions for Big Data management include multiple tools and platforms.

  • Assimilate and evaluate database performance across varying workloads

  • Reduce administrative, storage, development and server costs

With Clavax's Big Data
Management tools,
businesses can:
  • Achieve high-speed analytics with optimized analytics capabilities like deep analytics

  • Apart from harnessing the benefits of load-optimized systems, businesses can have the capacity to be up and running at all times.

Use Case Identification

Understanding the challenges that can be addressed with the implementation of Big Data Analytics is critical to simplifying IT infrastructure, innovating new business models and accelerating key business processes. It is high time that the big data market moves from learning about or experimenting with big data technologies. We highlight the top 5 use cases that can be your first steps into the world of big data.

  • Integrating multiple sources of internal as well as external data to generate a 360-degree view of the consumer

  • Augmenting cyber security with fraud detection, risk identification and real time monitoring of incoming or outgoing data streams

  • Exploring data to discover, visualize and understand all enterprise data to improve decision making

  • Integration and optimization of data warehouse capabilities along with big data to facilitate new forms of analysis

  • Analysis of sensory data to gain real time visualizations on consumer behavior, transaction, experience and operations

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