2017Unpublished venueRequires access

Predictive analytics in data science for business intelligence solutions

Parth Wazurkar, Robin Singh Bhadoria, Dhananjai Bajpai

Open publisher page 47 citations

Abstract

In modern era of computing, organizations are focusing on the better utilization of technology and surviving to gear-up with global business demand. Such competition is acting as a driving force for its business to cope-up the data which generated every second of minute. This data needs to figure out and segregated with information which is required for is business growth model. The Predictive Analytics (PA) uses various algorithms to find out different patterns in large data that might suggest the efficient behavior for business solution. This paper provides a conceptual decision making process for data using predictive analysis to maximize the success ratio for handling large dataset. Today, different technologies like cloud computing, SOA, are together transforming information technology but in turn, are imposing new complexities to the data computation. Due to such advances in technologies, and it requires rapid and dynamic data analysis for structured and unstructured data.

About this research paper

What this paper is about

In modern era of computing, organizations are focusing on the better utilization of technology and surviving to gear-up with global business demand. Such competition is acting as a driving force for its business to cope-up the data which generated every second of minute. This data needs to figure out and segregated with information which is required for is business growth model. The Predictive Analytics (PA) uses various algorithms to find out different patterns in large data that might suggest the efficient behavior for business solution. This paper provides a conceptual decision making process for data using predictive analysis to maximize the success ratio for handling large dataset. Today, different technologies like cloud computing, SOA, are together transforming information technology but in turn, are imposing new complexities to the data computation. Due to such advances in technologies, and it requires rapid and dynamic data analysis for structured and unstructured data.

Why it matters

OpenAlex reports 47 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

In modern era of computing, organizations are focusing on the better utilization of technology and surviving to gear-up with global business demand. Such competition is acting as a driving force for its business to cope-up the data which generated every second of minute. This data needs to figure out and segregated with information which is required for is business growth model. The Predictive Analytics (PA) uses various algorithms to find out different patterns in large data that might suggest the efficient behavior for business solution. This paper provides a conceptual decision making process for data using predictive analysis to maximize the success ratio for handling large dataset. Today, different technologies like cloud computing, SOA, are together transforming information technology but in turn, are imposing new complexities to the data computation. Due to such advances in technologies, and it requires rapid and dynamic data analysis for structured and unstructured data.

Key concepts: Business intelligence, Computer science, Predictive analytics, Data science, Business analytics, Big data, Cloud computing, Analytics

Related papers

Back to paper searchBrowse research topicsOriginal source
Predictive analytics in data science for business intelligence solutions — Research Paper | ScholarLens