Like bean dip and ogres, layers are the building blocks of the modern data stack.
Its powerful selection of tooling components combine to create a single synchronized and extensible data platform with each layer serving a unique function of the data pipeline.
Unlike ogres, however, the cloud data platform isn’t a fairy tale. New tooling and integrations are created almost daily in an effort to augment and elevate it.
So, with infinitely expanding integrations and the opportunity to add new layers for every feature and function of your data motion, the question arises — where do you start? Or to put it a different way, how do you deliver a data platform that drives real value for stakeholders without building a platform that’s either too complex to manage or too expensive to justify?
For small data teams building their first cloud-native platforms and teams making the jump from on-prem for the first time, it’s essential to bias those layers that will have the most immediate impact on business outcomes.