In about 10 percent of data warehouse projects, the selection of the platform and the related approach to the data architecture involve high-risk, critical decision processes. These risks must be assessed early in the development of your data strategy, and the associated decision processes must be integrated into strategy development.
There are two main factors that determine whether your project faces this higher level of engineering risk: scale and complexity. Whether these factors are present depends on the business purpose and role of your data warehouse, your business requirements, and the scale of your system operation over the strategic time frame. These factors apply both in the cloud and on premises.
If your project falls within this higher risk zone, the wrong data architecture or platform can sink it through unreasonably high costs, unacceptably poor system performance, or a badly compromised architecture that prolongs time to value and destroys agility.
In this workshop we will discuss this challenge and cover:
- Defining your business purpose and requirements as they relate to your data architecture and platform
- Assessing the data warehouse scale factor with regard to engineering risk
- Assessing the data warehouse complexity factor with regard to engineering risk
- The interaction of scale and complexity
- The process required to deal with these significant engineering risks early—so you can successfully enable your larger data strategy
The workshop will include presentations on these principles and practices, examples of data warehouse requirements which are (and are not) high risk in this sense, and facilitated exercises and discussions.