You need 2 types of people to keep early-stage startups from stagnating:
- someone who’ll shamelessly sell the product before it’s fully ready to be sold
- someone who’s embarrassed by this and will push to improve the product faster
Excited to share our first integration with @getdbt today! You can now build metrics directly on top of dbt models and enjoy lineage, freshness and soon lots more 🧑🍳
This is @prukalpa's "I have a dream" speech.
I have a dream where metadata is managed properly and accessible and updatable in context. Where new starters can be useful in less than 3 months and we don't waste time on stale centralised docs. 🙂
Second principle: all technical decisions are easy until someone's fingers touch a keyboard, and then the Sunk Cost Principle comes into full effect.
By the time we had Tableau up and running, we had already built like 30+ dashboards in Mode. It was over.
"The expected outcome of improving a stack — say, implementing CI/CD, adding staging environments, onboarding a new tool, hardening conventions, adopting infrastructure as code — is that over an extended period, the rate of value creation will increase." https://t.co/dJU532Tm9P
To my many friends/followers doing metadata/catalog startups, I have a request: please integrate the metadata info with my BI tool so that I can see it *while I am doing queries.*
I have no desire to *ever* visit a third website to just "browse the metadata."
@nick_handel at the Metrics Store Summit today
The era of metrics stores is making it easier for more organisations to benefit from advanced analytics tooling, that can integrate with these metrics stores.
Just read this blog from @HightouchData about need for speed in rETL - https://t.co/znDs4hxxAd They use @RocksetCloud as the source here but most companies are still building upon slow ETL batch systems. So much value to unlock by moving the data faster with little downside
"We know how to reason about the parts of the system that we are most familiar with, but we don’t spend as much time on the causal links and downstream impacts of changes in our metrics."
https://t.co/kVJVKQbeIn
@data_weekly thrilled to feature @DSJayatillake's data founder story: Read the exciting journey from Joining as a Cofounder after being an Advisor
https://t.co/YtUla0Tc2b
It’s Wednesday afternoon, and time for a substack post!
This time exploring my background in the commercial side of data and how this is my basis in understanding the value of data for an organisation.
https://t.co/ohKQW2LjNl
It’s Wednesday afternoon, and time for a substack post!
This time focused on data and analytics engineering! I’m expecting some 🌶 from software engineers who have zero tolerance of scope creep in any form 😂
https://t.co/qgttIXJaZJ
"One popular AI approach, machine learning (ML), can be combined with data, a business process, and an enterprise workflow to create the context to build a system of intelligence."
@jerrychen
@GreylockVC
@avora https://t.co/OoTef0rDvT
"all SaaS apps will get recreated as data apps - as apps on top of the data layer"
@martin_casado
https://t.co/yhTGtIK5k4
It's nice to be working on app that started on the data layer 😁
This is why I wanted to join @avora, we’re not building foundations any more; we’re starting to build the house.
Our products provide timely insights with context, saving our customers pounds and pence, dollars and cents.
https://t.co/Kwzym8MDMc