Metadata
- Author: Justin Gage
- Full Title:: Data as a Product vs. Data as a Service
- Category:: 🗞️Articles
- URL:: https://readtechnically.medium.com/data-as-a-product-vs-data-as-a-service-d9f7e622dc55?utm_source=pocket_saves
- Finished date:: 2023-10-09
Highlights
There are two broad mandates that data teams tend to get formed with (I’m being overly simplistic on purpose, bro): 1) Provide data to the company 2) Provide insights to the company (View Highlight)
the conflation of these two objectives is exactly what kills good data talent and confounds the hiring process (View Highlight)
It’s extremely rare to find exceptional data talent and exceptional functional talent together in the same human being. That’s why in practice these models are always mixed, but rarely well. (View Highlight)
(It’s rare that teams will be able to execute on DaaS without first mastering DaaP, and I’ve seen this problem first hand: data teams will try to grow into strategic decision support without rock solid reporting and data models, and it just doesn’t work (View Highlight)
To execute on a DaaS strategy, you’ll need to hire analysts and scientists who: • Deeply understand the functional area that they support (product, marketing, support) • Are able to communicate with stakeholders and really understand their needs • Handle long term, nebulously defined, strategic research projects with little direction — the opposite of pulling tickets off of a backlog (View Highlight)