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    • Crypto-Inspired Data Strategy: What Top Teams Do Differently

      This article explores how data teams can adopt strategic practices from the crypto industry, particularly MoonPay’s approach under Director of Data Emily Loh, to move beyond reactive tasks and implement a proactive, value-driven data strategy. It covers resource allocation frameworks, AI implementation, and system design principles to help teams operate more effectively in fast-changing environments.

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    • Breaking Free from Costly Data Migration Cycles

      A comprehensive analysis of how recurring data migration projects impact productivity and divert focus from strategic priorities. The article outlines practical methods to align migration efforts with measurable business outcomes, manage risk proactively, reduce unnecessary costs, and avoid vendor-imposed cycles. It offers expert perspectives on integrating migration planning into long-term infrastructure strategy to ensure continuity, scalability, and sustained business value.

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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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