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Research Paper | Information Technology | India | Volume 9 Issue 12, December 2020 | Popularity: 3.8 / 10

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Data Vault 2.0: Evolution and Adoption in Large Enterprises

Guruprasad Nookala

Abstract: Data Vault 2.0 represents a significant evolution in data warehousing techniques, offering a scalable, flexible, and adaptable framework designed to address the challenges of modern data management in large enterprises. Initially developed to overcome the limitations of traditional data warehousing methods like star and snowflake schemas, Data Vault 2.0 integrates agile methodologies, continuous integration, and automation to better handle the growing complexity, volume, and velocity of enterprise data. By utilizing a hub-and-spoke architecture, it decouples the business entities (hubs) from the context (satellites) and links them in a flexible, scalable structure. This approach supports an organization?s need for rapid change while ensuring historical data traceability and auditability, a critical component in today?s data-driven world. Large enterprises are increasingly adopting Data Vault 2.0 for its ability to accommodate frequent schema changes without disrupting existing systems. Its modular nature also facilitates the gradual build-out of data models, which is particularly beneficial for enterprises undergoing digital transformation or those with highly complex data landscapes. Additionally, Data Vault 2.0?s automation capabilities reduce the time and effort required to manage ETL (Extract, Transform, Load) processes, making it more efficient for large-scale operations. The methodology has been especially effective in industries such as finance, healthcare, and telecommunications, where regulatory compliance and data accuracy are critical. As enterprises continue to accumulate massive volumes of structured and unstructured data, Data Vault 2.0 offers a future-proofed, adaptive solution that aligns with the strategic goals of data-centric organizations. Through its emphasis on flexibility, scalability, and automation, Data Vault 2.0 is increasingly viewed as the next-generation data warehousing approach, equipping enterprises to meet evolving data challenges.

Keywords: Data Vault 2.0, Data Modeling, Data Warehousing, Business Agility, Scalability, Flexibility, Enterprise Data Management, ETL, Big Data, Data Integration, Data Governance, Data Lineage, Adaptability, Agile Data Warehouse, Data Vault Methodology, Data Automation, Metadata-Driven Approach, Large Enterprises, Real-Time Data, Cloud Data Warehousing

Edition: Volume 9 Issue 12, December 2020

Pages: 1866 - 1874

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