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🤖 What if you could make smarter decisions without writing a single line of SQL? In this episode, Vadym and Ruslan explore how augmented analytics is transforming how teams interact with data, making insights faster, easier, and more intuitive for everyone, not just analysts.
What you’ll learn:
✨ How “augmented” analytics differs from classic BI tools
🧠 Real-world examples of no-data-team teams winning with AI
⚠️ The biggest challenges – and how to overcome them
🚀 Where to start – and how to get adoption right
🧰 Tools like Google Dataplex, BigQuery, and beyond
➡️ Start making smarter decisions with OWOX BI
Vadym: Hey everyone, welcome back to The Data Crunch Podcast! I'm Vadym, and today we’re diving into a topic that’s honestly kind of magical – augmented analytics. Not in the sci-fi, flying-cars sense, but in the way it’s quietly transforming how people make decisions with data. And joining me today is Ruslan, Head of Product at OWOX.
Ruslan: Hey Vadym! Super excited to be back on the podcast. This is one of those topics I’ve been wanting to unpack for a while – it’s such a shift in how we think about data access and decision-making.
Vadym: Absolutely. We’re talking about AI, machine learning, and natural language processing – all baked into your analytics tools. But instead of it being complicated, it’s actually making things easier. More natural. Less effort.
And hey, before we dive deeper – if you're enjoying the show and want more real talk about analytics, decision-making, and smart data workflows, go ahead and subscribe to The Data Crunch Podcast. We drop a new episode every Thursday on YouTube and your favorite podcast apps.
Alright, so let’s kick this off. Ruslan, remember that time we were talking to a retail client who had zero data team, just a bunch of spreadsheets, and somehow they’d built out this wild dashboard system using our tool and a bit of augmented analytics?
Ruslan: Oh yeah, the one where their operations lead basically turned into an analyst overnight because she could just ask questions in plain English and get charts back? That was incredible.
Vadym: Right? That’s kind of the promise here – what if you didn’t need to know SQL to get real answers from your data?
Ruslan: And let’s be real – that’s a game-changer. For so long, analytics has felt like a walled garden. If you didn’t have the skills, you couldn’t play. Augmented analytics tears that down.
Vadym: Okay, so let’s break it down for our listeners – what makes this kind of analytics different from the classic dashboards everyone’s used to?
Ruslan: Three big things:
Vadym: And the wild part is that it doesn’t take a 10-person data team to make this stuff work.
Ruslan: Exactly. That’s the democratization piece. You can have one analyst, or even none – just people curious enough to ask questions. The system does the heavy lifting.
Vadym: Got it. I am curious, what’s your favorite example of that in real life?
Ruslan: Honestly? A finance team we worked with – just three people, manually pulling numbers every month, juggling Excel exports, copy-pasting like it was the early 2000s. We gave them an augmented setup, and boom – they had daily refreshed reports, anomaly alerts, and even a bot that summarized performance.
Vadym: And suddenly they had time to think instead of scrambling. That’s what I love about this stuff.
Ruslan: Yup. And if you’re listening and thinking, “Okay, but what do I need to try this out?” – here’s the good news. It’s already in tools like Dataplex from Google Cloud, BigQuery, and even some third-party platforms that plug into Sheets and BI tools. You don’t need to reinvent the stack.
Vadym: Dataplex is worth calling out – it handles data governance and metadata automatically, which is a huge win for anyone who’s tired of chasing down who owns what.
Ruslan: And BigQuery, of course, is the muscle behind it. Real-time querying at scale – with AI integrations baked in.
Vadym: Now, no surprise – this stuff isn’t all sunshine and rainbows. There are challenges. Where do you see teams struggle the most?
Ruslan: Let’s start with the obvious one – data quality. Garbage in, garbage out. If the inputs are messy, even the smartest tools can’t help.
Vadym: Totally. And I’d add user adoption. Sometimes you roll out these beautiful systems and... crickets. People are afraid to click anything.
Ruslan: Right, because if the tool’s too complex or feels like a black box, people won’t trust it. And then you’re back to spreadsheet hacks.
Vadym: So what’s the fix? I know we always talk about start small...
Ruslan: Exactly. Start with a real use case – a team that’s eager. Give them something useful right away. Once they see value, it spreads. Also: make feedback loops a habit. Ask what’s working, what’s confusing, and refine from there.
Vadym: Yes… And please – clean your data. Automate your pipelines. Set up governance. That’s the real foundation.
Ruslan: One more thing – augmented analytics works best when teams talk to each other. Sales sharing data with marketing. Finance is collaborating with ops. It’s not just about insights — it’s about shared language.
Vadym: Awesome. Before we wrap, what’s your big takeaway for anyone thinking about getting started with this?
Ruslan: Don’t overthink it. Augmented analytics isn’t just for tech giants anymore. Start with one decision you wish was faster or smarter. Try automating just that. You’ll be amazed what opens up next.
Vadym: Love it. And hey – if you're listening and thinking, “I want to make smarter decisions with less effort and more trust in my data,” check us out at owox.com. We build this stuff every day.
Ruslan: If you take one thing from this episode, let it be this: great insights don’t need to be hard. With the right tools and mindset, smarter decisions are totally within reach. And if you need a hand, OWOX is always here to help.
Vadym: That’s it for this episode today. Don’t forget to subscribe, drop us a comment, and we’ll catch you guys next week on the Data Crunch podcast!
