Rare Radiological Presentation of Spinal Cord Compression: A Unique Case of Osseous Metastasis from Primary Pulmonary Chondrosarcoma

Abstract

Arun Krishnadas

In this paper, the significance of data analytics for finance and business will be discussed, with a focus on innovation. The introduction provides a clear meaning of data analytics and points out its importance in decision-making. The literature review part of the book gives background information and analyses historical theories up to recent theories that encourage their application.

In this paper, the primary areas of using data analytics in financial decision-making are discussed and they include risk evaluation, investment measurement, and; fraud identification. Also, it explains how data analytics is used in business processes such as improvement operation efficiency, customer targeting, and supply chain. Business intelligence applications and big data frameworks are also described, as well as the difficulties that companies experience in employing them for data analytics.

Examples of sectoral data analytics applications are discussed with examples and detailed methodologies and results that have been achieved. Moreover, the paper also reveals emerging themes in data analytics, such as artificial intelligence integration, real-time, data governance, and ethics.

Thus, the study establishes the imperative for organizations to promote and adopt data analytics as a critical tool in improving organizational decision-making processes, innovation, and sustained organizational growth. Therefore, overcoming the barriers to implementation allows us to make the best use of data analytics and use data to drive changes across organizations.

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