All resources
📊 Ever feel like you're spending more time cleaning your data than actually using it? In this episode, Vadym and Helen dig into one of the most common — and costly — problems in analytics: fragmented, unreliable, and inconsistent data. Learn why business-ready data is essential for decision-making and how OWOX BI helps teams automate transformations, manage orchestration, and stay in control — all without needing a full data engineering team.
💡 What you’ll learn in this episode:
1️⃣ The key challenges in turning raw data into trusted insights.
2️⃣ How OWOX BI simplifies transformations, orchestration, and scaling analytics.
3️⃣ Why our new JS Data Connectors are a game-changer for analysts and marketers.
➡️ Start preparing business-ready data with OWOX BI
Vadym:
Hey everyone, welcome back to another episode of The Data Crunch Podcast! I’m Vadym, Growth Marketing Manager at OWOX, and today we’re tackling a topic that I know a lot of analysts and marketing teams struggle with — making sense of messy, fragmented data and turning it into reliable, business-ready insights.
And to dive into this super important topic, I’ve got our Head of Customer Success at OWOX, Helen, here with me today.
Hey Helen, great to have you on our podcast for the first time! I’m excited to explore today’s topic with you.
Helen:
Hey Vadym, always excited to be here. And honestly, this is a topic I’m really passionate about because it touches every part of data-driven decision-making.
You can have all the dashboards and tracking tools in the world, but if your underlying data is messy, inconsistent, or fragmented, it’s impossible to trust your insights. Good decisions start with good data — and good data starts with proper preparation.
Vadym:
Absolutely! I think every team at some point runs into that wall — where data looks great on the surface, but under the hood, it’s chaotic. Today, we're going to break down why that happens, the challenges teams face, and how OWOX BI makes the whole data preparation process smoother and faster.
But real quick, before we dive deep — if you’re tuning in on YouTube, don’t forget to hit that subscribe button and drop a comment about your biggest data challenge. And if you’re listening on Spotify, Apple Podcasts, or anywhere else, make sure to follow the show and turn on notifications. We drop new episodes every Thursday, packed with tips to boost your analytics game.
Alright, Helen, let’s kick it off: can you start by explaining what we mean when we talk about “business-ready data”?
Helen:
Sure thing! So, business-ready data is the final-cleaned, structured data that actually reflects how your business operates.
It’s not raw clickstream logs or messy CRM exports — it’s data that defines what a "user," a "transaction," or a "lead" means specifically for your business. This is critical because without a clear business data model, reports become inconsistent, mistakes multiply, and every new dashboard feels like reinventing the wheel.
Business-ready data is what lets you confidently build reports, send clean data to visualization tools like Power BI, Tableau, or Looker Studio, and — most importantly — actually trust the numbers you’re looking at.
Vadym:
That makes so much sense. It's like... without a shared model, everyone’s speaking a slightly different language, right?
Helen:
Exactly! And it doesn’t just cause confusion — it eats up a huge amount of time. Analysts spend half their week fixing inconsistencies instead of focusing on analysis and finding growth opportunities.
Vadym:
Right. And speaking of time drains, let's talk about the specific challenges analysts face trying to get data into a business-ready format. What's the first big hurdle?
Helen:
The first big one? It’s preparing business-ready data — meaning merging different data sources into a single unified structure.
For example, connecting user behavior across devices, linking session data to ad costs, creating user profiles... Normally, analysts spend days or even weeks building SQL scripts, pipelines, validations — and then maintaining them forever.
Vadym:
Yeah, and I imagine if one thing changes — like a new campaign or a new data source — you have to redo a lot of that work, right?
Helen:
Exactly. It’s not sustainable. That’s why OWOX BI helps automate these transformations.
With just a few clicks, you can:
All of this happens in an easy-to-manage interface — no scheduled queries or scripts, when you don’t even know when exactly your query will be executed, or a headache if you need to change something in all your connected queries and need to check and correct them one by one
Vadym:
That's amazing. It sounds like you're removing about 70% of the grunt work analysts usually have to do just to start analyzing.
Helen:
That’s exactly the goal — make it easy for analysts to be analysts, not just data cleaners.
Vadym:
Now I know another huge problem teams have — especially growing SaaS companies — is just controlling everything. You’ve got so many pipelines, queries, reports... it’s easy to lose track. How does OWOX help with that orchestration piece?
Helen:
Yeah, once your data setup gets complex, managing it manually becomes a nightmare.
That’s why in OWOX BI Transformations, you can view comprehensive logs, track dependencies, add and change the variables, manage SQL transformations, and immediately spot any delays or errors — all in one place with a really friendly, collaborative interface.
It’s like getting a bird’s-eye view of your whole analytics system, but still being able to zoom into the tiniest detail when needed.
Vadym:
I love that. It gives analysts real control without burying them in maintenance tasks.
And I guess the final big challenge is the shortage of data engineers, right? Especially when custom transformation tools like Airflow or dbt are too technical for analysts to manage alone.
Helen:
Exactly. Not every company has a full data engineering team. And honestly, they shouldn't need one just to clean and prepare marketing data.
OWOX BI makes analysts self-sufficient — they can set up, manage, and adjust data connectors and transformations themselves, without writing endless code or waiting on dev resources.
Thanks to our new OWOX JS Data Connectors, it’s easier than ever. They provide a lightweight, flexible way to pull data directly into your Google Sheets or BigQuery projects without heavy engineering work. It's a powerful, open-source solution designed for marketers and analysts to streamline data collection. That’s a massive shift in efficiency.
Vadym:
It’s a total game-changer.
By the way, if you want to try our free JS Data Connectors to export data from BigQuery into Google Sheets, check out the link in the description below.
Alright, Helen, before we wrap up — any final takeaways you’d want our listeners to remember?
Helen:
Just this: messy data isn’t just annoying — it’s dangerous. It slows down decisions, hides risks, and kills trust.
The faster and cleaner you can move from raw data to business-ready data, the more powerful your analytics will be.
And with OWOX BI, you can automate that journey — saving time, boosting trust, and letting your analysts focus on real growth opportunities, not cleaning up data messes.
Vadym:
Love it. Thank you, Helen — tons of great insights today! It’s great to have you here, joining our Data Crunch Podcast family.
And for everyone listening — if you’re tired of spending more time fixing your data than analyzing it, check out OWOX BI at owox.com. We make it easy to normalize, prepare, and orchestrate your data — and now with our free JS Data Connectors, you can pull data faster and smarter directly into your projects. The link is in the description — start for free today and see the difference!
Helen:
Thanks so much for tuning in, everyone. Stay curious, stay data-driven — and we’ll see you next time!
Vadym:
Thanks again for listening — and we’ll catch you in the next episode of The Data Crunch Podcast!
