Traditional data warehousing approaches are expensive, and they can’t cope with exponentially growing data of great variety and volume. This paper outlines principles and technologies for building the data warehouse of the future - the lean analytics platform.
Traditional data warehousing approaches can’t cope with exponentially growing data of great variety and volume. It needs to become lean and agile to support constantly growing and evolving analytics. Lean manufacturing principles have been increasing in popularity, and these ideas have been successfully applied to software development in the form of of agile-based frameworks. These methods are based on 3 key principles:
- Focus on Value
- Eliminate Waste
- Continuously Improve
Lean methods optimize software development, improve time to market, and reduce costs. Despite these successes, the majority of data warehousing and analytics development has traditionally used the waterfall model; lean methods have been difficult to adopt. This guide looks at the reasons behind that.