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.
Read the articleThis 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.
Read the articleThis 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.
Read the articleThis 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.
Read the articleA 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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