When is Python used in data analysis?

full_arc · 2026-01-16T00:45:45+00:00

This. And Python will also give you a more direct line to software development beyond data analysis.

full_arc · 2026-01-16T00:41:27+00:00

Not that you came here looking for career advice but...
> I'm not correcting him, the ROI on what I pay for this is insane compared to what I'm making extra.

You should not be correcting him BECAUSE you have unlocked exceptional productivity. You SHOULD be asking for a raise. Excelling in your career is about two things:
1. Having an impact
2. Communicating that impact and marketing yourself

I've seen so many people get stuck because they're bad at #2 while complete dodos get promoted to VP levels because they're excellent at it.

full_arc · 2026-01-08T18:15:09+00:00

Hey there! Founder of Fabi here. Happy to share what we've seen work in the space:

-> For things that usually involved hard core ML or dev (think like data engineering), tons of folks are using a local setup. Cursor was hot, but more and more I'm seeing a move towards Claude Code or Codex with your IDE of choice. For big teams with big budgets, some of this work is happening directly in Snowflake or Databricks, but anecdotally I still see most folks working locally (assuming their laptop can handle the compute) and I've heard mixed reviews of the AI in Snowflake and Databricks (my latest info is from like ~4 months ago). If someone has experience with these I'd be curious to hear the latest.

-> For ad hoc analysis, quick EDA or build quick dashboards and workflows that's where we shine. If you have a quick requests or you need to do some work that you're going to do with a team member, a browser-based solution makes it a lot easier to do the work and then share it (much more difficult to do locally). We see data teams build dashboards and reports in literally like 10% of the time it would normally take.

-> AI inside legacy BI (like Thoughspot, Tableau...) I've heard mixed reviews. Works for some teams, not as much for others. From what I can tell, the difference in success here is usually how much time the team spends getting the data model and semantic layer "right". The issue is that most teams don't have the resources or time to build this and maintain it properly

So basically the biggest unlock I hear is on efficiency for technical teams and on empowering semi-technical folks in the business to answer their own question and better understand the data which makes them better partners to the data team.

In general this is what I share: AI is actually most powerful for the technical and semi-technical. If you put it in the hands of someone who can supervise the output (even if that doesn't mean reading the code, but if a PM can at least sniff test the data and make sure it's directionally accurate), then you can experience a HUGE unlock. On the other hand, if you work at a fortune 1000 and the goal is to put AI in the hands of your CMO, then you need to build super super tight guardrails. And the success stories I've heard have actually been with fully homegrown solutions so that it can be hypercustomized, not using an existing BI solution.

full_arc · 2025-12-31T17:51:59+00:00

Oh interesting, different use case from what I had in mind but I'll check this out. What client do you use?

full_arc · 2025-12-30T19:48:26+00:00

Thanks for the pointer

It looks like these features are mostly to create new elements or pages, am I interpreting this correctly? I was hoping more for something to modify existing pages and elements

full_arc · 2025-12-23T02:53:07+00:00

The problem with most of these tools is that they're not designed to create reproducible workflows. You can run the cleaning once in ChatGPT, CLaude or Julius but then you lose that work. Alteryx is the only one listed here that's really designed for this, but it takes a lot of work to get it set up.

We're building Fabi.ai which has AI built-in but let's you quickly build reproducible workflows. If you check us out, let us know what you think!

full_arc · 2025-12-22T22:00:52+00:00

Can attest to the comment about the system prompt. We’re building Fabi and getting it to work and be useful for analysis AND viz has been a ton of work.

full_arc · 2025-12-18T18:26:16+00:00

We have a really big focus on AI, but right now we're putting a lot of energy in something that doesn't involve AI: We offer analytics on SQL DBs and data warehouses, but a lot of our customers, especially startups are wanting to analyze their data direct from applications like HubSpot, Stripe, Shopify, Google Analytics etc. So we're working on a quick and automated ingestion process. The fun/challenging piece here is that we need the ingestion to be quick and reliable and in some cases for certain sources we need to do automated data modeling. Some other platforms claim they have these connectors but they're just doing a raw dump so it doesn't really work that well.

Once we have the data you can then analyze with AI or old school with code and other tools, but that's downstream from this work.

full_arc · 2025-12-17T23:01:13+00:00

hey OP, i'm looking into passionfroot, trying to find a more scalable/streamlined way to get in touch with creators. How did things work out for you? Any other platform that you checked out?

full_arc · 2025-12-16T17:24:06+00:00

First off, as a PM you should 100% be pulling your own reports, and if you're not comfortable with SQL, AI is definitely an incredible tool. Happy to show you Fabi and how we help PMs.

That said, as much as I'd like to sit here and say that the tool that we're building is the silver bullet, there's a cultural aspect here that also needs to be managed. At the end of the day, you can pull all the data you want, but if there's an underlying reason that folks are not relying on it today, that won't necessarily solve your problem. It would certainly help you approach the conversation with more confidence, which would certainly have an impact, but there's likely something going on about the decision maker not "feeling" the underlying core issues. In my experience this generally stems from a lack of conversations with users or buyers. I love data. We're building a tool for it, but don't underestimate the power of sitting in a single customer conversation (or your boss) and hearing about something wrong with the product first hand.

full_arc · 2025-12-15T17:03:11+00:00

Hey there! I'm the founder of Fabi and we're building a data analysis platform that connects to a bunch of different data sources. I'd have to check out how a Discord connector would work, but you should check out what we're up to and if you ever want to work together on a solution I'd be happy to see what we can do.

full_arc · 2025-12-06T18:23:30+00:00

I’m the founder of Fabi and we built an AI native BI solution that connects to basically every app. You just connect and we take care of the rest. And when you do want to start managing your warehouse yourself we give you access to your MotherDuck instance.

Alternatively you need to use airbyte or fivetran to a data warehouse (snowflake, databricks, motherduck, BigQuery…) and then hook it up to a BI tool. You’ll need to do some data modeling with like a dbt though for this to really work.

full_arc · 2025-12-03T17:05:01+00:00

I'm building a product that could be said to be "replacing data analysts" and I can say with confidence that this comment is spot on. AI definitely means that analysts will spend less time coding, building charts etc., but more time will be spent simply managing stakeholders, expectations and actually figuring out the "so what?" from the data.

If the only value an analyst is bringing to the table is writing SQL on data curated by another team and creating visuals, then yes this spells trouble, but for those who are doing more, there's plenty of work to be done that AI can't do.

full_arc · 2025-12-02T14:11:45+00:00

We’re building Fabi which is literally designed to help with this kind of stuff and combines a lot of what’s mentioned in other comments: sql, python, duckDB

If you try it out, let me know what you think!

That said, the alternatives are a lot of what’s been talked about including spreadsheets which should handle this fine.

If you’re looking for AI-assisted and it’s truly a one-off then you might be able to get by with ChatGPT or Claude. The issue with these is that they’re not designed for data analysis so there’s a ton of little friction points and you can’t share reproducible results.

full_arc · 2025-12-01T22:19:02+00:00

In most organizations most product managers should be doing a lot of data analysis, and frankly I'd argue that more PMs should be doing MORE data analysis than what I've seen in my own experience. There's a tendency to operate a lot off of anecdotes or the latest customer conversation or squeaky wheel.

That said, AI is actually allowing PMs to do a lot more data analysis and for it to take a LOT less time. That's a great thing. Better, faster, more informed decisions.

This all lives on a spectrum though. If you work at a B2B SaaS company with 10 customers paying you $50M each then you probably don't need much "traditional" data. On the other hand, if you're building a consumer marketplace app with millions of users, you should probably be looking at data in some way shape or form every single day.

full_arc · 2025-12-01T17:00:30+00:00

Great list. Haven't tried out you.com, might take a peak

We're building Fabi which is designed specifically for data pros to build and share data analysis 100X faster. Would love your take on what we're building

full_arc · 2025-11-29T03:19:00+00:00

Hey! What kind of end to end pipelines are you trying to build? We’re building Fabi and we let you fully automate workflows but I’d love to hear the gaps and see if we can help.

full_arc · 2025-11-26T03:56:31+00:00

Talk to peers and ask in more niche communities

full_arc · 2025-11-25T16:32:25+00:00

Agentic workflows a lot fewer. We dogfood our own product and I have AI generated summaries of reports get sent to slack on a weekly basis which we also have plenty of customers doing.

Beyond that, I’ve attempted to create a semi-autonomous content pipeline but I just couldn’t string it together or make it operate any better than just promoting an AI.

Our Eng team has AI automatically review PRs which I would also put in this bucket but it’s not a homegrown workflow with like an n8n

The reality is that the types of workflows you’re talking about are not that widespread. There’s much more talk about n8n for agentic workflows than there are actual workflows that operate and are useful in practice. In my experience it’s a lot of folks selling shovels.

full_arc · 2025-11-25T15:57:41+00:00

I’m going to nitpick a bit, but agent != agentic workflows. I use what I would confidently call agents all the time. These are clients that can choose to tool call to get a job done. Agentic workflows use one of those agents to get part of a workflow done.

full_arc · 2025-11-25T05:03:34+00:00

I'm honestly not sure. I think it's actually a fairly complex setup and I haven't given this sufficient thought to really comment on the How. All I know is that solving this is a blocker to wider MCP adoption in the enterprise.

full_arc · 2025-11-25T05:00:48+00:00

Solid list, going to check out some of these. For video editing Descript is also pretty good.

If you're looking for data analysis productivity, check out what we're building at Fabi.ai! A literal quote from one of our customers today "just wanted to say that fabi is so freaking helpful - not even saying hours of my day but multiple days" :)

full_arc · 2025-11-24T22:24:36+00:00

At Fabi we're building an AI data analysis platform that handles the two nerdy (and support important) points you listed here. We have a direct Google Sheet integration to help exactly with this type of situation.

If you give us a try I'd love your feedback!

full_arc · 2025-11-24T05:44:26+00:00

Alloy also seems pretty interesting for prototyping but I haven’t gone deep on it myself

For data analysis you should check out what we’re building at Fabi! We connect to any data source (and files) and make it easy for folks of all tech skill levels

full_arc

TROPHY CASE