Exploring Data and AI With Databricks Community Edition

Summary

• Free tier learning platform: This video introduces Databricks Community Edition, providing a free, professional-grade environment for learning data and AI without cost barriers.
• Unified learning environment: The platform enables students, career switchers, and data enthusiasts to work with notebooks, load data, explore datasets, and train models in one place.
• Accessible data careers: This video shares lessons for starting a data journey and demonstrates how the free edition lowers barriers to entry for aspiring data professionals.

Exploring Data and AI With Databricks Community Edition

Talk by Will Valori, Senior Product Manager, Databricks
Join this video to see how you can get started with data and AI using Databricks Community Edition—free, and built for learners like you. You’ll get a first look at a unified environment where you can work with professional-grade tools to load and explore data, build notebooks, and train simple models.
Here’s more to explore:
Economist Impact: Unlocking enterprise AI: https://www.databricks.com/resources/webinar/unlocking-enterprise-ai
The State of Data + AI: https://www.databricks.com/resources/ebook/state-of-data-ai
See all the product announcements from Data + AI Summit: https://www.databricks.com/events/dataaisummit-2025-announcements

FAQs

Who should use Databricks Community Edition?

Students, career switchers, developers wanting to learn data concepts, business users seeking data insights, and anyone curious about exploring data and AI can use the free edition without cost barriers.

What learning resources are available in the Community Edition?

The Community Edition provides professional-grade tools including notebooks for code development, data loading and exploration capabilities, and simple machine learning model training in a unified interface.

What are the key lessons for starting a data career?

Start with questions rather than abstract theory, apply concrete skills to real problems, practice consistently, and use accessible tools to experiment. This removes confusion from the learning journey.

How does the Community Edition prepare users for enterprise use?

By providing real professional-grade tools and workflows in a free environment, learners develop practical skills that transfer directly to enterprise data engineering and analytics work.

Full transcript

So, hi, I'm Will. Uh, I'm a one of the product team at Data Bricks. Uh, so I'm the product manager for our free edition which we which we launched today. So, super exciting day for us today and uh very excited to talk to you all. Um, it used to be called the community edition. So, have you seen Yeah, you shouldn't be able to hear me. It's the headphones. Yeah. Yeah. Uh so yeah um used to be called the community edition.
So if you see that around and about it's no longer called that. It's called the free edition now. Um and this talk is all about how you can get started with data and AI using the free edition. Um so who's this relevant for? So the good news is more people than ever want to learn data and AI, right? So you might be a student or a career switcher. Uh you might be a developer who's trying to get a little bit more data oriented, learn some stuff about agents, perhaps a business user trying to get insight from data decision maker or just someone who's kind of curious and wants to explore.
And so if you identify with any of these uh then you've kind of come to the right place. So in this talk we're going to we're going to talk through how to do it and it leans a little bit on my experience developing this but then also uh a little bit on my own personal journey. I describe myself maybe as a kind of intermediate level data person. You know, I'm not wildly skilled. I'm not the best uh you know, data analyst out there in the world.
Um but I've taken this kind of long and meandering journey to uh to learn data. Uh and I wanted to share a few lessons and then a simple path to get started today. Um so I started and I had this kind of dark and winding path which was just question after question. So you know where should I actually start? Why do I need to download things? What language should I choose? And there were just many questions like this. What if I break something again and again and again and again?
And I found that it was just a super opaque process to know how to get started with stuff. From that, I kind of crystallized these four kind of golden rules for how you get started in a data career or a data passion. um and I'd love to share them with you and then uh finally uh we can kind of walk you through how you guys can get started on the free edition. So lesson number one is start with questions not theory. So it's very tempting to start with this kind of very abstract stuff looking at coding language maybe ma like meandering around in code academy or something like that but if you do that you you very quickly lose momentum and the key thing you need is uh momentum for like I guess I'll call it like a feedback loop uh between motivation and momentum you start with a little bit of motivation if you don't get a quick win early you'll lose momentum and momentum is what's going to keep you going in this journey so start with questions and try and get a question answered in 5 minutes to prove to you that you can do it.
Hot tip number two is use tools that get out of your way. So this is about momentum as well. So if you use a tool where the first step is downloading something, connecting to a cloud infra, you've already lost. You're already grappling with configuration with infrastructure and you're not learning actual data skills. Similarly, on the opposite end of the spectrum, I would say avoid sandbox tools as well. Okay? Because you'll outgrow sandbox tools really quickly.
They won't feel real. Third rule is let the LLM teach you. This has been the thing that's been the biggest unlock for me is being able to use LLM uh to make progress. LM is the most extraordinary tool for learning. You can ask any question and they can really guide you through the data process. We got really three kind of LLMs that I love to use. The first is the data bricks assistant. The second is the genie and then finally of course good old chat GBT.
Um this is like number one thing for unlocking and unblocking I'd say. And then final golden rule four or four is just do it. So I first got interested in data in about 2011. It wasn't until about 2018 that I then picked something up. So it's very easy to just spend seven years procrastinating, not doing anything. You just got to get started, get going. Um, so now we can think about how you actually do that. So the exciting news that hopefully you saw in the keynote, this is a kind of massive moment in data and AI.
Uh, today data bricks is basically making almost all data bricks features fully available and alluded to this in the keynote. Uh, but pretty much anything that you want to do in data bricks you can now do for free in a personal capacity. So we call it data bricks free edition. It's modern data bricks. It's completely free. You can explore the full data and AI life cycle. So any part of the uh you know data and AI journey.
And then finally it's browser based. You don't need a credit and you don't need to set up any infrastructure at all. There's no downloading. It's super simple. You can get in in about 60 seconds and start running your first query. This is a massive moment for data bricks, massive moment for data and AI education. And it's just a super meaningful thing to be able to share it all with you. So what do you do with data bricks free edition?
Well, quite quickly you can get started and kind of wet your appetite as a as a data and AI learner and prove to yourself that you actually can do this because I think that's one of the key blockers that people have. It's very simple. You're going to create your account. That's like creating any other account. Takes 30 seconds. You're going to pick a cool data set that you're interested in. Just pick anything that any topic that you like and find a data set on it.
Ask your first question of that data. If you're less technical, you can start in natural language with something like data bricks gener. I can show you how to do that. If you're more technical, you can get straight into the SQL or the Python. Then run your first query. So this is stepping out of natural language into something a little bit more technical. Uh and then finally visualize your insight. create a graph or something to make it real and to be able to communicate it.
If you do these five things, I would positate that you are then a data practitioner. You do that, you're done it, you've done your job, you're ready and you can go out into the world and kind of master this craft. And the nice thing is you can do these things in the space of about 10 minutes. So hopefully I can prove that to you today uh with the data bricks free edition. So we can switch over now to a to a demo and I'll walk you through guys through exactly how you do this.
Um so the first thing first step was create your account. Uh so to create your account you just go to this is maybe the most self-explanatory part of the entire talk. You just go to databicks. com and you create an account. So you can click try data bricks up here. You'll get to the account creation page. At the moment the free edition because it's just launched is a little bit hard to spot on this page. This is probably the hardest thing that you'll do in this whole journey.
It's down here. So, this is where you're going to go. You can click click there to get to your free account. Uh, and you'll just land on a pretty standard signup page. You can create your account, set up your workspace. Takes 30 seconds, 45 seconds. I already have an account, so I won't make you guys look at this. Um, but once you create your account, you end up in essentially a full data bricks workspace that looks a little bit like this.
Mine's a little bit more evolved. I've already got some data in there, but essentially at this point you you have your data bricks account and you can move on to step two which is picking a cool data set. There are three kind of sources of data sets you can use. So the first is you can look for our samples. So if you go in the catalog here uh we'll have some sample data just here. Uh and you can explore this. We got some real data from acue weather.
If you're passionate about the weather like my dad then you could explore that. But if you're less interested in that, we've got some other sample datas, some New York taxi data set and so on. Second source of data is the uh the data bricks marketplace over here. This is a place where people can share uh you know data or or or notebooks or analysis with each other. Um the top tips I would say for this page firstly filter by products.
So filter for a table and then secondly filter for free stuff and then immediately you get all these different free data sets that you can use which is really good. Um so for example maybe I'm really interested in in zip codes for one use or another. You can click in you can see a little bit about what fields you have in this data. Um, and very quickly and hopefully uh hopefully we won't suffer too much with the 10,000 people who are com competing for Wi-Fi in here.
I think we might with this spinner, but essentially very quickly you can load this into your uh into your workspace. Um, and that's how you get kind of marketplace data in. And then the final thing is if you want to go outside and you have a really narrow specific thing for example like I'm a bit of a tennis fan and I like tennis data you can go to Kaggle and Kaggle has this amazing data set kind of repository. Some of it's live and updating.
You can just download a data from there and upload it back into data script. So already over here uh we're through the first two steps here and we're ready to ask our first question of our data. And the way that you do that uh is you can use Genie. Genie is my favorite way to do this incredible tool. It's a AI natural language way to query data. So I'm just going to go and create a Genie room here and show you how powerful this is uh to get yourself started on uh your data and AI journey.
So I've got got several spaces here. A space is kind of like one chatbot where you can ask uh questions of your data. I'll create a new space. I think you might remember earlier I mentioned I'm kind of interested in tennis. So I'm going to create I'm going to create a space that looks at my tennis data set. Um and this is a data set of all the tennis matches um in the last 25 years. Um and this is where I can start. You can see I have this chatbot interface and I can start to look at my data and ask questions of it.
Um so for example I could say uh give me the top 10 players by number of matches one and I can just ask that question and this is where this like true data bricks magic comes in. So this is a text to SQL tool. Um, it's going to think about my request and it's going to translate into SQL and then it's going to run the query and just like that I can see, wow, has the most tennis match matches one of anyone closely followed by Jovovich and Nadal and they're way ahead as a as a big three in the 21st century.
So just like that, you've got your first data insight and we're probably three minutes into demoing this tool. So that's how easy it is to become a data professional in this modern day and age. The next thing that I want to do is start to run my first query. So this is taking me out of English and into more technical skills. Now of course you don't necessarily need to do that in this day and age. But I think it builds confidence as you go.
So one thing I can do is I can show the code here that Genie called and immediately I can see you know exactly what happened. Okay. So we had a w a with and then we had a we selected our data um and then we kind of ordered it by uh by number of wins. I can copy this data uh and I can create a notebook uh and start exploring uh exploring this more. So if you create a notebook again, we're going to suffer with the Wi-Fi a little bit, but we're getting there.
And I can just copy this data into this notebook or this query rather. And the one thing I think I'm going to need is yeah, this should just uh run again. Like there's no no need to set up any infrastructure here. Uh it should just I didn't run it. So Oh yeah, there you go. Data bricks is going to handle all the complexity for you. So you can be a pure data practitioner. You don't have to worry about uh you know how compute works or have setting up an AWS account, anything like that.
Um you can just get in and uh and run it. So there you go. We've now connected to compute. Um and now this uh this query is running. Um and hopefully relatively soon that should um that should uh that should calculate. So we can come back to this in a minute. Um step five is visualize your insights. So there's a number of ways you can do this in data bricks. You can visualize inside notebooks. You can visualize that inside the SQL query editor.
Um but I also really like uh using dashboards. So I'll show you a dashboard while this query runs and then we can come back and do that. So on the left hand side here we have dashboards. I'll open a new tab so we can come back here. Dashboards are the best way to visualize data. You can share them throughout your organization. And I have a couple of sample data uh dashboards here. So if I just show you this one, I think again this will take a moment to spin up because we have uh we have Wi-Fi uh issues.
But this is going to load. This is going to connect to data and it's going to load a data set for um for dashboards and I think my other query is cooked so I'm bouncing around a little bit but so there you go. So this is the kind of thing you can do as well. This is all pretty straightforward. I'll show you how to create one of these charts. Um but again things like dashboards, data visualizations, all of this you can learn just by getting stuck in in in this data uh data bricks tool.
Um, so I won't build one of these entirely in front of you because I want to leave some space for Q&A. But if we go back to our notebook here, we can see that this is um, this is now calculated. Our queries worked and we can also visualize it ourselves. So to create your first visualization, all you do is click plus here and you can add a visualization and our visualization editor is pretty smart. Um, so quite quickly you can uh you can create charts and it'll understand exactly how you should do it and so on.
Um, so if I just click save, there we have our first visualization. So if we think about what we've done, you know, we created our account, signed up, found a question we're interested in, and we've been able to answer it in five minutes and visualize it. This is incredibly powerful tool. Um, and it's much much less difficult than it was, you know, yesterday, but certainly five years ago. So I hope that the main takeaway you guys take from this demo is that this is a really uh this is something you're really capable of.
You can do it. You should feel very empowered. I feel everyone can be a uh you know data practitioner in uh in 2025. So I'd really just encourage you guys to give it a go, sign up uh and uh see what you can do. So uh the way you do that you can I've got a QR code here and I'll present this just so you can do it. So you can scan that QR code or you can go to signup. databicks. com and remember it's just that hidden click here link in the bottom right.
Um, and it's as simple as that. And you guys can, you know, within 10 minutes or 15 minutes of this course uh talk, you should be uh creating your first visualizations as well. Um, so thanks very much for listening. We got a few minutes left uh to do Q&A. So happy to do that as well.

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