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Ask HN: What does your BI stack look like?

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Re: Ask HN: What does your BI stack look like?

#121

Post by thingsilearned »

throwaway49409 wrote: post #21

how does one end up doing BI | Data Engineering ? currently a frontend | full-stack JS dev. tired of that world and want to switch to something stable ?

If you're already doing engineering work you may be able to just go get a job focusing on data - if you're upfront about wanting to learn. I've found most people have learned the skills on the job. Besides the books mentioned I commonly recommend these resources

DataCamp.com has some great courses

Tableau has some great online education - many people learned BI from them

Many free resources for getting started with data at different levels (note: this is one of my sites) https://dataschool.com

Description of common roles in BI/data: https://chartio.com/learn/data-analytics/distinguishing-data...

Re: Ask HN: What does your BI stack look like?

#122

Post by dwl285 »

alexfromapex wrote: post #30
dwl285 wrote: post #28

If you have a data team: Stitch / Segment -> BigQuery -> Dataform -> BigQuery -> Looker I work with many companies helping them set up their data stack, and from what I've seen this is pretty much the optimal set up. These tools all require very little maintenance, are relatively cheap (compared to the man power required to set these things up from scratch internally), and scale well as companies grow and complexity…

Thanks for sharing, I don’t think there’s an “optimal setup” in the objective sense but good to know this works well.

Good point. I guess I mean, if you put a gun to my head and forced me to pick one, this is what I'd pick (and I think it works for a pretty meaningful percentage of companies that are looking for an answer to the original question)

Re: Ask HN: What does your BI stack look like?

#123

Post by salsakran »

Dwolb wrote: post #86
mazameli wrote: post #77

Earlier quoted context omitted.

UX guy from Metabase here. Glad to hear it's working well for you. Happy to answer any questions folks might have.

Wow great to see you in the thread. No questions from me but great job on the latest update.

Thanks!

-Another Metabase team member

Re: Ask HN: What does your BI stack look like?

#124

Post by TraceOn37 »

We built a tool to help non-technical folk transform their data into useful formats for BI (https://www.data-monkey.com). The tool currently supports JSON, CSV, Excel and text files, and comes with features to merge/filter/transform data. It's free to try and use if you're interested - we'd love to hear your feedback!

Re: Ask HN: What does your BI stack look like?

#125

Post by jconley »

App, Web, IoT device send realtime events to a fluentd system with many events going to Segment. Web front end also loads Segment for various ad trackers. IoT device also uploads telemetry and other logs in both realtime and asynchronously and those end up in some Postgres databases.

Segment syncs our event data periodically to our data warehouse (Redshift).

We have a readonly replica of the eCommerce DB for live stats (Postgres).

And there is a time series db for system/IoT telemetry (InfluxDB).

Most of our BI queries are done in Mode. Some are done in Grafana (data in our InfluxDB and some live data). Spot check against Google Analytics or FB ad tracker...

Re: Ask HN: What does your BI stack look like?

#128

Post by [deleted] »

grahamdietz wrote: post #44
dwl285 wrote: post #28

If you have a data team: Stitch / Segment -> BigQuery -> Dataform -> BigQuery -> Looker I work with many companies helping them set up their data stack, and from what I've seen this is pretty much the optimal set up. These tools all require very little maintenance, are relatively cheap (compared to the man power required to set these things up from scratch internally), and scale well as companies grow and complexity…

^ Dataform is cool. Check them out.

[deleted]

Re: Ask HN: What does your BI stack look like?

#129

Post by rajivayyangar »

netcraft wrote: post #103
rajivayyangar wrote: post #82

As a data scientist (startup / Yahoo) turned product manager (4 startups), I've used a variety of stacks in the past - from plain SQL, to Mode, to Mixpanel, Looker, Interana, and Hive. Recently we started using PopSQL ( https://popsql.com ) and love it. When I don't have a dedicated data team, my philosophy is: 1) Make it difficult to get wrong answers - Don't use Google Analytics. It's too easy to generate incorrect…

$20/user/month seems incredibly expensive for an editor that we would have traditionally paid a one time cost for. I assume this has the saving and sharing of queries built in, but that is a lot of money for some storage. Are there other major benefits I am not seeing? (It is not my intention to attack you or make you defend this product, I am just curious if I am missing something - there are a lot of similar produc…

Saving, shared queries, easy link sharing, and basic charts with some intelligence. It also has excellent query UX (auto-complete, etc.).

Most of all, it's really fast. It fundamentally depends on your DB of course, but PopSQL doesn't add any extra bloat the way Mode does.

Re: Ask HN: What does your BI stack look like?

#130

Post by apinstein »

seveibar wrote: post #13

Postgres -> Metabase I believe this is the best combination of cheap/powerful for early-stage startups. My very non-technical cofounder is able to use metabase's simple GUI interface to create graphs/insights (even joining and aggregating across tables!), and for anything complex I can step in a give a helper SQL query. We have around 10M records we aggregate around for daily insights. Metabase can also be run as a p…

+1 for metabase. I’ve deployed it at 2 companies. The latest version allows you to compose “questions” you create in the system which is really powerful for organizing layers of data reporting.

Also, their API conforms 100% to Zapier’s polling feed structure, and I managed to build an integration that syncs our customer base to Pipedrive in a few hours. A bit more time and I have it automatically moving deals along in the pipeline as users progress with using the product. That alone was game changing for our customer success team.

Thanks, team Metabase!

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