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Abstract
In the fast-paced financial world we live in today, companies are feeling more pressure than ever to handle huge amounts of data that are incredibly varied and change rapidly. They need to do this while being quick to react (agile) and keeping costs down. The older ways of building data warehouses, which often rely on structures called Star and Snowflake schemas, just aren't really built to handle these modern demands. They tend to be too rigid and require a lot of ongoing work. This article takes a close look at the Data Vault 2.0 design pattern as a solution for building data warehouses that can grow (are scalable), be flexible, and are easy to audit – all things needed in data warehousing today, particularly in the financial sector. We're going to dig into the limits of those older architectural styles, introduce you to the main ideas and parts that make up Data Vault 2.0, talk about how you can actually put it into practice (including how automation plays a big role), examine the benefits it offers in managing complexity and making sure everything is compliant with rules, touch upon some potential difficulties you might face, and think about the return on investment (ROI) for companies that decide to go with this approach.
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