Why Automating Patterns in your Data Vault is the Key

Why Automating Patterns in your Data Vault is the Key

Data Vault is designed to maximize the return on investment in an organisation’s data analytics setup,

It can help the data team organise the data in a way that reduces the impact of change on the data model, importantly it is pattern based and lends itself to automation – to enhance the performance of the data team. Data Vault is a data warehouse methodology, developed by business intelligence thought-leader Dan Linstedt, that allows the data to be captured with the correct business keys and relationships within the enterprise. This enables more accurate and useful analytical results that can help improve efficiency and savings in various areas of the business, such as operations, production, distribution, sales, marketing, finance, or human resources (HR). It is all about capturing the essence of each business unit through precise business keys and relationships, paving the way for meaningful analytics that drive operational savings across the board.

For organisations with legacy databases, transitioning to an automated Data Vault requires a significant upfront investment. However, the long-term benefits of such a transformation can far outweigh the initial costs.

This Data Vault User Group meeting spotlighted a novel approach by software engineer Sriram Nutulapati. His method leverages Data Vault’s automated patterns to construct solutions more efficiently, promising a swifter return on data analytics investments. The solution was proposed by software engineer Sriramn Nutulapati, who is pursuing a master’s degree in data science at the University of Minnesota and works for Target corporation, and Sreeni Nutulapati, director of strategic initiatives at Illumifin. Both enthusiastic about data applications and solving enterprise challenges using architectural patterns that suit the technology of choice – so that organisations can get a quicker return on investments in data analytics. In the session, they discussed the challenges of building a Data Vault that can leverage the patterns without creating too many expensive changes on the enterprise model, which can take a lot of time and resources within any data team. They also showed the presentation that demonstrated how to implement their automated pattern-based approach.