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!
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.”
MVF is a global customer generation platform that depends on fast, accurate data pipelines to drive reporting and marketing performance across multiple regions and channels. Their ETL spend had nearly tripled under a new pricing model, creating unsustainable cost pressure. Costs were escalating faster than business value, engineering teams were stretched, and they needed a simpler, more sustainable approach.
MVF is a global customer generation platform that depends on fast, accurate data pipelines to drive reporting and marketing performance across multiple regions and channels.
Their ETL spend had nearly tripled under a new pricing model, creating unsustainable cost pressure. Costs were escalating faster than business value, engineering teams were stretched, and they needed a simpler, more sustainable approach.
As Andonis Pavlidis, Head of Data at MVF, explained: “Prices were always increasing, SLAs were dropping. It didn’t feel like a partnership anymore, but rather like a commodity.”
MVF’s data team was under increasing strain from a fragile and inefficient ETL setup.
MVF partnered with Matatika to deliver a risk-free migration strategy that cut costs and simplified infrastructure.
As Andonis Pavlidis noted: “We loved working with the Matatika team as they felt an extension of our team. They shared the same frustrations and reacted as we would react ourselves.”
The migration delivered more than savings. MVF gained faster pipelines, stronger reliability, and greater team productivity. Is this better?
As Andonis Pavlidis concluded: “We went to Matatika for a migration. We ended up with an improvement of our stack.”
Fivetran connectors migratedGoogle Adwords, GA4 Export, Iterable, MySQL (x12), Facebook Ads, Appwiki, Bing Ads, Webhooks, Outbrain, Taboola, Twitter Ads, TikTok Ads, LinkedIn Ads, Google Sheets, S3 and Dbt Cloud Reporting.
Custom Airflow connectors migrated to Matatika supported connectorsAirtable, Five9, Survicate, Everflow, Injixo, Invoca, Custom S3.
New connector developedBaidu and CallMiner
MVF’s migration spanned a wide range of connectors across marketing, customer interaction, compliance, and operational data sources, together accounting for more than 1B rows per year.
| Category | Example Connectors | Estimated Rows / Year |
| Marketing & Paid Media | Google Adwords, GA4 Export, Facebook Ads, Bing Ads, TikTok Ads, LinkedIn Ads, Outbrain, Taboola | 600M |
| Customer Interaction | Iterable, Five9, Survicate, Everflow, Invoca (real-time + historical) | 250M |
| Sensitive / Compliance Data | Webhooks (disposition bronze), Airtable, Injixo | 120M |
| Operational / Other Sources | MySQL (x12), Google Sheets, S3 Export, Dbt Cloud Reporting, ExpertReview S3 | 30M |
| New Development | BaiduCall MIner | Included above |
The term “zero-risk ETL transformation” may sound ambitious, but it’s real, proven, and achievable. With Matatika’s phased rollout, rigorous testing, transparent pricing, and post-deployment efficiency, it’s no longer a buzzword, it’s best practice. ETL doesn’t have to be hard. It just has to be done right.
Data is as essential to manufacturing today as any raw material. Yet, while most manufacturers generate valuable data across their operations, fragmented and siloed systems often keep them from putting this information to effective use. Matatika’s ETL (Extract, Transform, Load) solution is designed specifically for manufacturing’s data challenges, enabling teams to unify, automate, and harness real-time insights across their operations.
SaaS ETL Tools pricing is broken. Too many businesses are stuck with platforms that charge by rows, gigabytes, or arbitrary metrics, pushing costs higher without delivering real value. It’s a model that inflates SaaS data costs, forcing companies to pay more for data that doesn’t always lead to better insights.
Managing large amounts of data can quickly become expensive, especially for companies using platforms like Google Analytics 4 (GA4) in Snowflake. Many ETL platforms charge based on the volume of data processed, leading to high costs without added business value. At Matatika, we offer a solution that helps you save up to 99.4% on GA4 costs while maintaining high performance. Here’s how our cost-based pricing model works, and why it's more effective than traditional ETL platforms.
Imagine a modern, centralised platform that integrates commercially supported ETL (extract, transform, load) connectors / plugins and reputable open-source ETL tools. This platform would streamline data management by unifying data from various sources, ensuring consistency and reliability. Not to mention, the fixing of any fundamental data accuracy issues in the process.
This blog aims to clarify what ETL has meant traditionally, and what modern ETL tools can do for operational efficiency and tech-ROI right now. We’ll also go over the key considerations to help you opt for a top set of tools, and importantly – the right partner...
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ImpactGrows helps corporates achieve their sustainability goals with an end-to-end platform for automated reporting, management, and deep analytics of Environmental Social, and Governance (ESG) information. A company embarking on a sustainability journey needs to consider its maturity, community sentiment, peer benchmarking, materiality mapping, goal setting, strategy & risk. At every step, trusted data is key to tracking, decision-making, and evidencing sustainability-linked lending - a $1.6 trillion lending product in 2021.