Related posts for ‘#Blog’
🔔 Celebrating a Most Eventful Matatika Year! 🔔
The Matatika Year in Review: On the Twelfth Day of Data... As the year wraps up, we’re taking a lighthearted, musical look back at the incredible journey we’ve shared! Thanks to the energy and support of our amazing community, 2025 has been an absolutely unforgettable year of growth, connection, and major milestones. Grab a hot drink, and join us as we sing the praises of the Matatika year that was!
Building Data Platforms That Actually Solve Business Problems
Meet Teddy Bernays Teddy is a highly autonomous Freelance Data Engineer and Google Cloud Trainer who focuses on helping startups and mid-sized companies build efficient, scalable, and cost-effective data platforms. He started his career in the complex world of audio engineering before transitioning to IT, where he found a fascination with the mechanics "under the hood" of data systems. Today, he is a firm believer that the solution to data inconsistency isn't always more code, but more clarity. His approach is simple: “If it’s simple, do it simple. You don't need three different tools to solve a one-tool problem.”
Looking for Arch?
Arch has officially shut down, and the Arch platform is no longer operating. If you’re an Arch customer looking for what’s next, you’re in the right place. Matatika is now supporting former Arch customers and helping teams continue their analytics and data workflows without disruption.
Arch has officially shut down, and the Arch platform is no longer operating.
If you’re an Arch customer looking for what’s next, you’re in the right place. Matatika is now supporting former Arch customers and helping teams continue their analytics and data workflows without disruption.
In addition, Matatika has acquired the Meltano open source project, ensuring its continued development, maintenance, and long-term sustainability. Meltano remains open source, community-driven, and is now backed by a team focused on stability, extensibility, and enterprise-ready data tooling.
If you were using Arch or Meltano and need guidance, migration support, or want to learn how Matatika can help you move forward, we’re here to help.
Welcome to the next chapter.
Google Sheets for Analysts: How to Eliminate the Data Update Bottleneck
The Ticket Queue That Never Ends
Your analyst sends a Slack message at 9am.
“Hey, can you update the product-to-GL mapping table? Finance added three new categories last week and our revenue reports are off.”
It’s a five-minute job. You know exactly what needs doing. But you’re in the middle of debugging a pipeline issue, and context switching now means you’ll lose an hour getting back to where you were.
“I’ll get to it this afternoon,” you reply.
By 2pm, you’ve forgotten. The analyst follows up at 4pm. You finally do it at 5:30pm, right before you are about to leave. The analyst thanks you, clearly frustrated that a simple update took all day.
The next week, same analyst, different request. Update the territory assignments. Then the customer segment definitions. Then the exchange rates. Then back to the GL mappings because something changed again.
You’re not a data engineer anymore. You’re a ticket processor for data updates that shouldn’t require engineering at all.
Stop Manually Uploading Spreadsheets: 5 High-Impact Use Cases (and How Resident Advisor Fixed It)
If your week still includes exporting CSVs and uploading them into dashboards, you’re paying a “data tax” in delays, context switching, and stale numbers. Here are the top five use cases where teams should replace manual uploads with a real Google Sheets → warehouse pipeline plus a quick look at how Resident Advisor (RA) made this work in production.
Aftermath of the DBT + Fivetran Merger: What It Really Means for Data Teams
Two weeks on from the DBT + Fivetran merger, and the dust hasn’t settled, it’s only just starting to reveal what comes next. The deal didn’t just merge two companies. It merged two very different philosophies about how modern data should move, transform, and deliver value.
Build Strategy First. Choose Technology That Deserves It
Introduction Every organisation has lived this story. A new data platform or AI tool promises to fix everything. Budgets are approved, contracts are signed — and a few months later, the same problems remain. Dashboards don’t align, pipelines still break, and confidence in the numbers keeps slipping. For Dylan Anderson, Head of Data Strategy at Perfusion, the real issue isn’t the technology itself — it’s where teams choose to begin. “Vendors are great at selling the idea that their product will solve all your data needs,” he says. “But strategy isn’t about buying more tools. It’s about helping the business reach its goals using data, technology, and AI in the right way.” In this episode of Data Matas, Dylan joins host Aaron Phethean to explore why strong data strategies always start with purpose, and how honest, outcome-driven technology earns its place in the stack.
How high-performing data teams align business goals, data strategy, and technology to build trust that lasts
The Smart Way to Connect Mixpanel to Your Revenue Data
Mixpanel gives you brilliant product analytics. Funnels, retention, user journeys. You can see exactly what users do in your application. But as teams mature, they start asking questions Mixpanel can't answer on its own. Which users are most valuable? Which marketing campaigns drove high-value customers? How does feature usage correlate with revenue? The most valuable insights come from connecting Mixpanel data to the rest of your business. User behaviour linked to revenue outcomes. Product engagement joined to marketing attribution. Feature usage correlated with customer lifetime value. That's what becomes possible when you extend Mixpanel with a warehouse-first approach.
How to Do Even More With Mixpanel Data
Mixpanel gives you brilliant product analytics. Funnels, retention, user journeys. You can see exactly what users do in your application. But as teams mature, they start asking questions Mixpanel can't answer on its own. Which users generate the most revenue? Which marketing campaigns drive engaged customers? How does feature usage correlate with support tickets or churn risk? The most valuable insights come from connecting Mixpanel data to the rest of your business. That's what becomes possible when you extend Mixpanel with a warehouse-first approach.
How to Scale Mixpanel Data Efficiently Without Spiralling Costs
Your product's growing. More users, more events, more insights flowing through Mixpanel. That's exactly what you want. The problem? As your Mixpanel event volume increases, your data infrastructure costs often grow faster than your revenue. High-volume, append-only event data breaks traditional ETL pricing models. Every duplicate event costs money. Every unchanged property gets billed. Growth becomes a financial penalty. There's a smarter way to handle event data at scale.