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Trapped by Your ETL Tool? How Mirror Mode Helps You Switch ETL Tools Without Risk
The blog highlights how legacy ETL tools lock teams into costly, inefficient row-based pricing and risky migrations. Matatika offers a solution with Mirror Mode, allowing companies to run both ETL systems in parallel—risk-free and free until go-live. This eliminates disruption, double payments, and uncertainty. With transparent, performance-based pricing, Matatika typically cuts ETL costs by 40–60% while improving speed and support, giving data and finance teams a safer, smarter path to switch.
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Data Analytics Strategy: How Quantum Thinking Enables Change Without Disruption
This article explores how quantum thinking can inform a modern data analytics strategy, enabling teams to innovate safely without disrupting existing operations. Based on insights from David Draper, Data Science Manager at Iris Software Group, it offers practical guidance on modular system design, embedding innovation in delivery cycles, and improving AI explainability. Ideal for data leaders seeking resilient, forward-looking analytics strategies.
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Stop Fixing Data Pipelines – Start Driving Strategy
This article examines how unreliable data pipelines can trap data teams in endless maintenance work, draining strategic capacity. It explores practical solutions for building resilient, self-healing pipelines, allowing engineers to focus on delivering insights and driving business growth.
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Why Data Migration Tools Fail? Here’s How to Make Them Work
This article explores why data migrations, despite good intentions, often fail to deliver real value, and how using the right data migration tools strategically can change the outcome. Drawing on real-world insights, it offers practical guidance for data leaders looking to break the cycle of reactive migrations and build more resilient, scalable systems.
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Crypto-Inspired Data Strategy: What Top Teams Do Differently
This blog explores how MoonPay's Emily Loh uses a disciplined data strategy to drive innovation, improve focus, and future-proof infrastructure. Her 20/40/40 model and AI-first framework offer a replicable path for mid-level data leaders.
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