Ask HN: What's your startup's BI tool/setup?

[corrius]

I am a software/data engineer who is stepping up as the responsible of data in a 30-person startup and one of the first assignments is to choose and get up and running a BI tool so people that don't know SQL can explore data, create/look at dashboards and export data.

Now that I am looking into this problem I am curious what are other startups solutions to this.

- Is the CTO or one of the engineers taking requests and running queries and sending csv/excel files back?

- Do business people at your company know SQL so they can run their own?

- Do you run your own BI tool? If that's the case, which one? I guess most startups at this level don't need a BI tool but we have do as we have a strong business side and no-one knows SQL outside the engineering team.

[Jugurtha]

We integrated Airbyte, Superset (https://superset.apache.org) , and Streamlit (https://streamlit.io/) with our ML platform, (https://iko.ai).

The platform provides real-time collaborative notebooks so people can train, track, package, deploy, and monitor machine learning models on Kubernetes.

Depending on the client and their data sources, our people can get data using Airbyte. Then build dashboards using Superset. They also can deploy a Streamlit application right from the notebook without worrying about spinning up a VM on GCP, set the environment, deploy, add authentication, etc. as the platform does that. They can invoke the deployed models from there.

Especially with projects that move fast, the cycle needs to follow to show results to our clients and we shave off inefficiencies as we go.

[johntdaly]

At my previous company we used Tableau for a while and I was rather happy with it. I’m not sure what they are using now but I also build an excel exporter for common data and we also produced an excel file by hand for analysis so I would guess they are using excel now.

I honestly would suggest to use a BI tool rather than going with excel but you might be forced in one or the other direction based on what the people in your company are more comfortable with and how good or bad you data is. The quality of our data was bad enough that a manual step was required and more people where comfortable with excel.

I personally would go with BI tool. Like I said, I liked Tableau but from what I’ve seen MS PowerBI is also nice even though you will bind yourself to SQL Server. I would recommend Apache Superset as a no cost/low cost alternative. Tableau was expensive and because of that the people who where most interested in using it didn’t get the licenses and the people that got the licenses where not as interested. Also the licensing structure for Tableau is more suited towards larger companies and I personally think that BI tools are way to useful to limit them to management because of licensing cost.

[anakaine]

My organisation has both Tableau and PowerBI. The only reason I have not dropped Tableau (as the principle account and contract holder) is that PowerBI licensing is restricted by users, whilst Tableau Server has an unlimited model.

[johntdaly]

So you don’t get a licensing key you can reassign to another user for PowerBI? (that the way I read that)

[ReDeiPirati]

It looks like you have a strong self-service requirement ("so people that don't know SQL can explore data, create/look at dashboards and export data"), in that case I would encourage looking for BI tools like Metabase, Superset, etc...

At my previous company, we self-hosted Metabase using terraform on AWS, and connected it to a read-only replica of our production db. We also connected all the 3rd parties sources (Intercom, Zendesk, etc...) using Segment by moving the data to Redshift, which was connected to Metabase as well.

We created a Cloudflare tunnel (legacy) so that only people from the org could have access to Metabase via their Google profile.

It was a quite simple setup, but it worked very well for us.

[corrius]

I forgot to mention on the posts what are my thoughts so far:

- License products such as Tableau, Qlikview or PowerBI are too big for us at the moment, both in size, pricing, complexity, etc.

- Scheduled exports to Excel/csv don't solve our use-case as it needs our interaction every time there is a new export or change in the queries.

- Accepting requests directly don't scale well either.

- Currently we are considering Metabase, Superset and Redash. Leaning towards Metabase based on better UI, runs well in AWS and connects to SQL databases, Mongo, Redshift and Clickhouse (Not that we use all of them but we may in the future)

[pkalinowski]

40 people web startup. Currently Metabase as main BI tool, but I'm thinking about introducing a tool like hex.tech. IMO classic BI and dashboarding is inflexible and future lies somewhere else.

Backend is Bigquery + dbt. I highly recommend Bigquery if you are on GSuite and use Sheets. You can create views or tables in bq and have them included in sheets, always up to date. With dbt you can have them tested and be sure data is always correct.

True single source of truth, even for coworkers who work with excel only

[shiv86]

" BI tool so people that don't know SQL can explore data, create/look at dashboards and export data." - We had exactly the same requirement. Use Looker, its expensive but worth it. The requests to our data team has reduced by 90% We are a small startup with 20 employees

[huy]

If you're new to the BI space, this book should give you a pretty good high-level overview: https://www.holistics.io/books/setup-analytics/

[grolle]

We use a custom service that works similar to Segment (i.o.w. 500 loc that receive events and forward them to all sorts of systems).

We then have Mixpanel for simple stuff and a big sql database that we use for research using SQL, PowerBI, Grafana for more complex things.

[JasonCannon]

My startup is a bit different, because we actually have a BI team that offers custom BI dashboards for our clients. We use PowerBI Premium to embed our BI dashboards into our web application.