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Scaling Data Pipeline Architecture Without Excess Cloud Costs
An in-depth exploration of how organisations can scale their data pipeline architecture while maintaining strict control over cloud expenditure. The article provides actionable strategies to identify cost inefficiencies, transition from always-on data syncing to smart scheduling, renegotiate vendor contracts for flexibility, and integrate AI-driven automation into pipeline operations. It presents a structured roadmap to optimise infrastructure, enhance performance, and support agile growth without compromising budget discipline.
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How to Deliver a Zero-Risk ETL Transformation
Let’s be honest—ETL transformations have a bad reputation. Talk to any data leader, and they’ll tell you the same thing: it’s too disruptive, too expensive, and too risky. They worry about downtime, getting locked into another overpriced vendor contract, and the strain on internal teams. That’s exactly why at Matatika, we’ve built an approach that eliminates these risks entirely—no downtime, no wasted spend, and no surprises.
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7 Data Strategies That Work – What the Best Data Teams Do Differently
Every data team wants to scale efficiently, reduce costs, and deliver real business value. But in practice, many struggle with siloed workflows, unreliable data, and costly inefficiencies. Since recording Season 1 of the Data Matas podcast, I've reflected on the key levers these great teams are using to deliver value in their businesses and pulled together the seven of the biggest lessons. These aren’t abstract theories—they are practical, tested strategies from professionals who have made data work for their organisations.
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Transforming Manufacturing Data Management with Matatika’s ETL Solution
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.
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Why SaaS Data Pricing Models Are Costing More Than They Should
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.
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