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Applying Lagrange Model to Fill Data During Big Data Streaming

  • Sindhu P. MenonEmail author
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 39)

Abstract

Advancements in technology have significantly reshaped the social and economic environment. Businesses are coming up with new strategies to uncover hidden information from data in order to support better prediction and analysis. Data continues to grow at a rapid rate and it has become necessary to process the quality data. In mission critical applications, streaming of data plays a very important role. Discontinuity in data stream is unaffordable as it consumes more time and money. This paper proposes a technique through Lagrange’s Interpolation, which could avoid discontinuity in data streams when large data is being processed.

Keywords

Big data Velocity Lagrange’s Interpolation Streaming 

Notes

Acknowledgement

I would like to extend my gratitude to the members of PRO-ACT who have developed the data set used in this work. PRO-ACT (Pooled Resource Open-Access ALS Clinical Trials Database) contains about 8500 records of ALS patients whose identity is hidden.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Jain College of Engineering and TechnologyHubliIndia

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