Workday Prism Analytics: Leveraging the Power of One for Comprehensive Data Management

Authors: Monu Sharma

DOI: https://doi.org/10.5281/zenodo.14183852

Short DOI: https://doi.org/g8rc5v

Country: USA

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Abstract: This paper examines the integration of Prism Analytics with Workday, emphasizing the "Power of One" concept in the context of cloud computing. By unifying data acquisition, preparation, transformation, and publishing, organizations can leverage this application to harness the full potential of their data. Workday provides a robust foundation with its comprehensive human capital management and financial data, while Prism Analytics enhances analytical capabilities through advanced data processing tools. The paper discusses the streamlined workflows for data ingestion and transformation, highlighting best practices for ensuring data quality and integrity. Furthermore, it explores how the cloud-based architecture facilitates real-time data access and collaboration across departments, enabling organizations to publish actionable insights efficiently. Ultimately, this prism empowers decision-makers to make informed, strategic choices in a competitive landscape, demonstrating the critical role of cloud computing in modern data analytics.
Workday Prism Analytics helps solve these problems for finance and HR teams. It simplifies systems for IT, reduces costs, and makes it easier to manage old systems. With Workday Prism Analytics, finance and HR have a centralized data hub within their main system. This allows them to access the data they need securely, without losing accuracy, and provides user-friendly tools to easily generate insights from different data sources. This means better business decisions and improved performance like never before.

Keywords: ETL, Analytics, Workday, Prism, Integrations, ERP, AI, ML, Databases, Dashboard,HCM

Paper Id: 231582

Published On: 2021-04-06

Published In: Volume 9, Issue 2, March-April 2021

Cite This: Workday Prism Analytics: Leveraging the Power of One for Comprehensive Data Management - Monu Sharma - IJIRMPS Volume 9, Issue 2, March-April 2021. DOI 10.5281/zenodo.14183852

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