Latest Posts

Posts, news and updates

Thoughts from the Supersimple team on the data space, updates from the product and much more

How we use Supersimple at Supersimple
November 5, 2024

How we use Supersimple at Supersimple

One of the coolest things about building something like Supersimple is getting to heavily dogfood our own product. Here's how.

"People don't know the right questions to ask"
October 2, 2024

"People don't know the right questions to ask"

"People don't know the right questions to ask from their data" is something I've heard countless "data people" tell me. Yet, I've never seen it to be true.

Self-service BI 101 for B2B SaaS teams
August 26, 2024

Self-service BI 101 for B2B SaaS teams

What does truly self-service Business Intelligence look like and how can B2B SaaS startups use it to turn data into an unfair advantage?

Why I Never Used Data as a Product Manager
May 28, 2024

Why I Never Used Data as a Product Manager

I never used data as a product manager. I felt guilty about it, yet I didn't even ask others for help. Here's why.

Announcing Supersimple and $2.2M in funding
April 2, 2024

Announcing Supersimple and $2.2M in funding

We’re excited to announce Supersimple, a powerful data platform that lets anyone answer complex ad-hoc questions in minutes.

First Impressions of Early-Access GPT-4 Fine-Tuning
March 19, 2024

First Impressions of Early-Access GPT-4 Fine-Tuning

GPT-4 fine-tuning is starting to roll out in limited early access, and we've been experimenting with it for a while now. Here are our learnings about the performance leaps, the cost and latency of the latest-and-greatest fine-tuneable general purpose LLM.

Intro to Semantic Layers
April 23, 2024

Intro to Semantic Layers

The hottest thing in data over the past few years has been the "modern data stack". While having a neat data warehouse certainly feels nice, semantic layers might offer hope of actually making the data usable.

Data Teams Shouldn't Be Firefighters
March 19, 2024

Data Teams Shouldn't Be Firefighters

How can data teams transition from putting out never-ending fires to empowering the rest of their company to use data?