3 ms·

I'm giving up Power BI and I'm moving to Domo. I look at rolling my own occasionally.

_boffin_ 3y ago
We have Domo at work and it just seems overly complicated and insane. I'm wanting to learn it instead of just polling data sources and adding them to a local Opensearch instance, but... too verbose for me.
RedShift1 3y ago
If you want to roll your own, maybe have a look at Plotly's Dash?
- chatmasta 3y ago
  Observable Plot [0] is also nice. AFAIU it's the same library powering the visualizations within Observable itself. [0] https://observablehq.com/plot/ https://observablehq.com/plot/
mritchie712 3y ago
(I'm the founder of a competitor to Domo) I really like the concept of Domo. They have ETL, modeling, a warehouse and BI in one app ("data-stack-in-a-box"). I've interviewed 20 of their customers and the general sentiment was pretty bad. There's a long sales process, a longer process to get it set it up, and they've built all the modeling and connectors themselves (vendor lock in, none are best-in-class). Definite (https://www.definite.app/ https://www.definite.app/) is a data-stack-in-a-box. We have a built-in modeling layer for core metrics and an AI assistant to answer any one-off questions. A few ways we're different: Built on open source - We run the data stack for you and give you a single app to manage and analyze your data, but it's all built on open source standards. So if you decide at any point you want to run it all yourself, the code is yours to lift and shift to your own infrastructure. Battle tested connectors - We're using Meltano / Singer (open source library from Stitch) for our connectors, so they've been used heavily in production for years. Self-serve that actually works - A lot of tools promise self-serve, but AI is making this real. We've invested heavily in making it possible to ask questions and get accurate answers. The AI queries a modeled view of your data that can answer questions that depend on well defined metrics (e.g. ARR, DAU, etc.).
- danr4 3y ago
  all that text and no pricing page. shame.
  - mritchie712 3y ago
    Fair point! We have a free plan (capped at 3 users) and paid plans (which add ETL and a data warehouse) start at $500 a month.
- philipodonnell 3y ago
  > Text to SQL that actually works. Ask questions in natural language across multiple tables and our engine knows where to join. Can you share any information about how it knows where to join?
  - mritchie712 3y ago
    We do a couple things here: 1. When you bring your own data warehouse, we parse the query history, convert it so an AST and learn JOIN's from there 2. When you're using our managed data warehouse and ETL, we already know most of the JOIN's (e.g. we know how to join the Hubspot data we ingress to Stripe) 3. For anything not covered by #1 or #2, we have a modeling layer where you can specify how to join tables.

We have Domo at work and it just seems overly complicated and insane. I'm wanting to learn it instead of just polling data sources and adding them to a local Opensearch instance, but... too verbose for me.

RedShift1 3y ago

If you want to roll your own, maybe have a look at Plotly's Dash?

chatmasta 3y ago
Observable Plot [0] is also nice. AFAIU it's the same library powering the visualizations within Observable itself. [0] https://observablehq.com/plot/ https://observablehq.com/plot/

mritchie712 3y ago

(I'm the founder of a competitor to Domo) I really like the concept of Domo. They have ETL, modeling, a warehouse and BI in one app ("data-stack-in-a-box"). I've interviewed 20 of their customers and the general sentiment was pretty bad. There's a long sales process, a longer process to get it set it up, and they've built all the modeling and connectors themselves (vendor lock in, none are best-in-class). Definite (https://www.definite.app/ https://www.definite.app/) is a data-stack-in-a-box. We have a built-in modeling layer for core metrics and an AI assistant to answer any one-off questions. A few ways we're different: Built on open source - We run the data stack for you and give you a single app to manage and analyze your data, but it's all built on open source standards. So if you decide at any point you want to run it all yourself, the code is yours to lift and shift to your own infrastructure. Battle tested connectors - We're using Meltano / Singer (open source library from Stitch) for our connectors, so they've been used heavily in production for years. Self-serve that actually works - A lot of tools promise self-serve, but AI is making this real. We've invested heavily in making it possible to ask questions and get accurate answers. The AI queries a modeled view of your data that can answer questions that depend on well defined metrics (e.g. ARR, DAU, etc.).

danr4 3y ago
all that text and no pricing page. shame.
- mritchie712 3y ago
  Fair point! We have a free plan (capped at 3 users) and paid plans (which add ETL and a data warehouse) start at $500 a month.
philipodonnell 3y ago
> Text to SQL that actually works. Ask questions in natural language across multiple tables and our engine knows where to join. Can you share any information about how it knows where to join?
- mritchie712 3y ago
  We do a couple things here: 1. When you bring your own data warehouse, we parse the query history, convert it so an AST and learn JOIN's from there 2. When you're using our managed data warehouse and ETL, we already know most of the JOIN's (e.g. we know how to join the Hubspot data we ingress to Stripe) 3. For anything not covered by #1 or #2, we have a modeling layer where you can specify how to join tables.