International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 3 May-June 2024 Submit your research before last 3 days of June to publish your research paper in the issue of May-June.

Building Flexible, Data-driven Framework for Real-time Analysis

Author(s) Srikanth Iyengar, Yash Shingade, Ayush Singh, Kailas Devadkar, Jignesh Sisodia
Country India
Abstract In the contemporary business landscape, the escalating demand for real-time predictive analytics is driven by the imperative for dynamic decision-making. Traditional analytics models often prove inadequate in addressing the need for agility required to respond swiftly to rapidly changing circumstances. Real-time predictive analytics, however, offers a transformative solution, empowering organizations to make informed and timely decisions in fast-paced environments. This capability proves invaluable in industries were staying ahead of emerging trends is critical, fostering a proactive approach to decision-making that can significantly impact competitiveness.

The sheer volume and diversity of data require sophisticated solutions for processing and analysis. Real-time predictive analytics becomes an indispensable tool, offering the capability to promptly extract valuable insights from massive datasets. This not only enhances decision-making but also allows organizations to stay ahead by uncovering trends and patterns in real time.

Scalability is a fundamental consideration for organizations on a growth trajectory. Real-time predictive analytics frameworks provide a scalable foundation, allowing businesses to seamlessly expand their analytical capabilities. This adaptability ensures that the framework can handle the increasing demands for processing power and storage, aligning with the evolving needs of a growing organization.
Keywords Real-time Predictive Analytics, Dynamic Decision-Making, Big Data Frameworks, Data Stream Processing, Agile Analytics, Scalable Data Processing, Data Visualization, Data-driven Frameworks, Massive Dataset Handling, Flexibility in Analytics, Adaptable Systems, In-memory Processing, Strategic Planning
Field Computer > Data / Information
Published In Volume 6, Issue 2, March-April 2024
Published On 2024-04-15
Cite This Building Flexible, Data-driven Framework for Real-time Analysis - Srikanth Iyengar, Yash Shingade, Ayush Singh, Kailas Devadkar, Jignesh Sisodia - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.16532
DOI https://doi.org/10.36948/ijfmr.2024.v06i02.16532
Short DOI https://doi.org/gtq3d7

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