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Area of Big Data

Real or near-real time information delivery is one of the defining characteristics of big data analytics.

Research and development activities of the Big Data and Business Analytics Group are organized into six focus areas. The visual below shows these focus areas. The top three focus areas in the visual cover the core issues in big data life cycle from acquiring data to extracting business value from it. The bottom three areas cover the use of analytics in specific industry domains.This focus area addresses IT issues in managing the life cycle of data. This includes innovations in distributed /parallel and in-memory architectures, acquiring and integrating external data such as from social media, managing the allocation and movement of data across various tiers of the architecture, and optimizing the execution of data-intensive workflows.

NCPL-Big-Data-Applications

Big data methods and techniques

 

This focus area is about discovering novel methods and techniques for exploring, analyzing, and visualizing large sets of data. The team is engaged in evaluating and optimizing the performance of data mining, machine learning algorithms and other techniques from statistics and operations research area in a distributed environment such as Hadoop.

Big data value management

 

The transformative potential of big data lies in treating data as an asset. Extracting the most value out of data assets requires a data driven business strategy, a value-framework for data, assessing, valuating, realizing, complying, securing, and sustaining the value of data. These are all areas for development of best practices and innovation.

NCPL is equipped with where-with-all to handle your data analytics projects.

Service analytics

 

Many lead adopters of big data strategies have succesfully demonstrated the huge benefits of using big data analytics in the service sector. Marketing departments have used predictive analytics to design effective marketing campaign; customer service centers have become more efficient by a single view of the customers; and social media content has been analyzed to understand trends. In spite of a fair amount of work in this area, there is still many areas for improvement and innovation.

Health care analytics

 

Both health care research and health care systems generate a massive amount of complex data. From managing electronic medical records, provide better access to health care to understand complex drug interactions, and genomics, the opportunities for using advanced analytics are plentiful.

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