Dashboards Are Dead: Sigma’s BI Revolution for Trillion-Row Data
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Why does Mike Palmer say traditional BI has become boring?
Welcome
to
the Matt Podcast. I'm your host, Matt Turk from Firstmark.
What is the true definition of business intelligence according to Sigma?
Today, I'm sitting down with Mike Palmer, the CEO of Sigma Computing, a BI startup that recently accelerated to over $100 million in annual recurring revenue after closing a big $200 million round of financing less than a year ago. Now, Sigma is reinventing BI by enabling anyone with spreadsheet skills to analyze massive amounts of data in Snowflake or Databricks in seconds.
How did Sigma’s origin story with Sutter Hill and the Snowflake echo shape the company?
No SQL sorcery required. We'll unpack why Mike calls Tech2SQL chatbots the best executed terrible idea ever.
Is the ultimate hubris of engineering. This is not what AI was supposed to do for end users.
How a storyline from J.P.
Why does Sigma claim the spreadsheet problem hasn’t changed since 1985?
Morgan sparked Sigma's mission. The world did not need another BI product. J.P.
Morgan that told us that,
and I think
he was right.
Why he calls Microsoft Fabric old products in a shiny wrapper.
What motivated Sigma to reboot its product during the COVID‑19 lockdown?
They basically take an old product like Power BI, they throw Excel in there, some sort of connection to open AI, and they wrap it all into a marketing term called Fabric, and they charge you more money for it. And
why the modern data stack is headed
for massive consolidation. Things like semantic layers, data catalogs, ETL tools.
What are Sigma’s core architectural choices (no caching, no federation) and why?
It's far too fragmented. If you were to fast forward three years from now, you'll see many of these categories rolling into smaller numbers of categories.
This episode was recorded live during a recent Data Driven NYC, our monthly data and AI meetup in New York, hosted in partnership with our friends at Foursquare. If you care about BI, AI, or just want to understand the data gold rush, stick around for this very entertaining and insightful conversation with Mike. Mike, welcome. You have on the Sigma Computing website a line that I found super interesting, which is, forget the past 20 years of BI.
How does Sigma’s spreadsheet‑style interface scale to trillion‑row datasets?
It's been boring. What do you mean by that?
We talk about the fact that the world did not need another BI product. We didn't come up with that line. It was actually someone from JP Morgan that told us that. And I think he was right. BI as an industry is boring. The idea that And I know I'm in an audience of data people. Some of you have done this job, so no offense intended.
Why does Mike consider text‑to‑SQL AI a “terrible idea” for enterprise BI?
But when we were living in this world of client, you had storage and compute on premises. And you had to figure ways to connect to those things. And that was difficult from a security point of view and a networking point of view. And then you had these special skills like writing SQL. And then you could create dashboards for people who really wanted the data. That just didn't seem like a great model. combined with the fact that increasingly strangely over time, the chart became the proxy for the data. It's funny because if you look at older BI tools like BusinessObjects and even MicroStrategy and Qlik, they were very tabular in terms of their interface. And they gave you row level data. And then we sort of, in my opinion, devolved into Tableau.
And we sort of treated people like they were idiots and all they could really understand was a colorful pie chart. How do you really feel about Tableau? Actually, I tell everybody this. I'm very kind about my metaphor. If you've ever traveled to Japan and bought anything, they wrap things to within an inch of their lives. It could be a toothbrush, but you're gonna get that thing perfectly wrapped. And I think that Tableau is wrapping paper in Japan. You really wanted the toothbrush, but somehow what you really got was wrapping paper. And one of the things that we aspire to is just realize that you don't need the wrapping paper if you could really get a great toothbrush. We want people to interact with the data directly.
We wanted to recognize that the vast majority of people actually do their jobs in spreadsheets. Like the most common feature in all BI products was the button that said download to Excel. And that's how we did our jobs. So we wanted to change that, not be another BI company, it's boring. We wanted to be something very different. And I'm sure we'll talk about that here. Okay, and maybe to take a step
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Chapters
8 chapters
1
Why does Mike Palmer say traditional BI has become boring?
0:00–0:10
2
What is the true definition of business intelligence according to Sigma?
0:10–0:35
3
How did Sigma’s origin story with Sutter Hill and the Snowflake echo shape the company?
0:35–0:51
4
Why does Sigma claim the spreadsheet problem hasn’t changed since 1985?
0:51–1:02
5
What motivated Sigma to reboot its product during the COVID‑19 lockdown?
1:02–1:19
6
What are Sigma’s core architectural choices (no caching, no federation) and why?
1:19–2:00
7
How does Sigma’s spreadsheet‑style interface scale to trillion‑row datasets?
2:00–2:24
8
Why does Mike consider text‑to‑SQL AI a “terrible idea” for enterprise BI?
2:24–41:31
Speakers
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