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Sreeni and Sriramn Nutulapati
Model-Driven Data Vault Construction
A Data Vault allows us to organise the data to minimise the impact of change on a model. This pattern, if used, can act as a basis for both transactional and warehouse use cases on modern platforms that minimise data movement, so we can construct once and use it for all the data use cases. The challenge here is unless we approach converting existing databases that are primarily relational to Data Vault in an automated way, it requires a steep investment that can practically outweigh the benefits of Data Vault in the short term.
What if we could construct a Data Vault using patterns in an automated way?
This presentation discusses those patterns and a practical implementation of them.
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Model to Code
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Faster, simpler Data Vault builds & updates
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Agile Warehousing
Introducing the Presenter
Sreeni and Sriramn Nutulapati
Sriram - Software Engineer
Sreeni - Director, Strategic Initiatives
Sriram Nutulapati is a Software Engineer at Target corporation and he is currently pursuing a master's degree in Data Science at the University of Minnesota. He loves learning about data and its applications, as well as how it can benefit the world.
Sreeni Nutulapati, Director, Strategic initiatives at Illumifin, is passionate about solving enterprise challenges using architectural patterns that naturally fit the technology of choice so organisations get a faster ROI on their investments.
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.
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