Designing and Expanding a Scalable Data Dictionary for Established and Emerging Data Pipelines

Venkat Kalyan Uppala

Abstract: This paper explores the process of developing and expanding a data dictionary that can efficiently accommodate the intricacies of both legacy data structures and emerging data streams. It delves into the methodologies for cataloging data, ensuring consistency, and maintaining data quality across diverse and evolving data environments. By examining best practices and drawing on industry experiences, this paper provides a roadmap for organizations to create a scalable data dictionary that supports robust data governance, enhances data accessibility, and fosters a deeper understanding of the data assets within the organization. The effective management and utilization of data are crucial for organizations aiming to leverage data-driven insights for strategic decision-making. One essential tool in achieving this is a data dictionary-a centralized repository that documents data elements, their definitions, relationships, and usage across various systems and pipelines. As organizations grow and their data ecosystems become more complex, building and scaling a comprehensive data dictionary that can handle both existing data pipelines and new data sources becomes increasingly challenging.

Keywords: data dictionary, data governance, data management, scalable data, strategic decision-making

How to Cite?: Venkat Kalyan Uppala, "Designing and Expanding a Scalable Data Dictionary for Established and Emerging Data Pipelines", Volume 8 Issue 10, October 2019, International Journal of Science and Research (IJSR), Pages: 1884-1887, https://www.ijsr.net/getabstract.php?paperid=SR24827135009, DOI: https://dx.doi.org/10.21275/SR24827135009