Data warehouse projects are notorious with business stakeholders for taking too long and delivering too little value. Moving away from waterfall-style projects to an agile, iterative approach helps IT deliver on-target solutions to the business, develop faster and with lower risk and cost.
With data warehouse automation, your DW/BI staff no longer needs to produce quick fixes that lead to data inconsistency, drop braindead causing manual coding, avoid shadow IT and endless discussions with the business about lagging deliveries. Instead, they will focus on optimum modelling, data quality and other, more exciting stuff that has been neglected in the process.
The generation of any data warehouse model: E/R, data vault and star schema as well as the source to target chain of the data flow by generating the ETL will free your analytics staff from coding. This full lifecycle management is made possible by built-in methodologies and best practices. The metadata driven approach facilitates documentation and lineage. In conclusion: reduce project risk, cost and delivery time so you can focus on quality, relevance and user friendly delivery of information to the business.
Mike Ferguson is a pioneer in business intelligence/analytics, data strategy and data management. He will be teaching Data Warehouse Modernization (25 and 26 May) and Practical Guidelines for Implementing a Data Mesh (26 and 27 June) in Amsterdam.