Assumptions about Data Platform Architecture Scaling-Out is better than scaling up. In-Memory is better than on disk (spinning or otherwise). Having data hosted within your control plane or tenant, either on-premises or in the cloud (AWS, Azure, GCP) gives you more control and visibility into the security and access for this data than data hosted […]
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Assumptions about Change when working with data Always be flexible because technology and vendors are constantly changing and evolving. Be a life-long learner because if you are not keeping up with the advancements in your industry, technology, tools, etc. then you are being left behind.
Object Stores are better because: Cloud storage in object storage (AWS S3, Azure Storage, Google Cloud Storage) is widely used and it has well defined standards and protocols. Object Storage has the best cost structure of any data storage mode/method. Object Storage allows separating Data Storage from Compute which eliminates inefficiencies when both share a
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Assumptions about Code when working with data Owning your code is better than Renting, Licensing, or Subscribing to someone else’s code. Code built to perform an operation like ETL based on patterns and driven by property files and parameters to repeat the same operation on thousands of tables/files/objects is more consistent and efficient, easier to
Assumptions about Platform/Vendor Agnostic standards, structures, tools, and languages: Open standard formats, structures, tools, and languages are better than proprietary vendor specific formats, structures, tools, and languages. The ability to move data, code, workflows, processes, and solutions between vendors and platforms without re-architecting or lengthy migration efforts provides the flexibility needed to consider and change
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