Analytics Technology Value Matrix 2023

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Over the past few years, the way that enterprise and mid-market customers produce and consume analytic content has changed, and customers increasingly leverage higher-order analytics and data science methodologies to identify business opportunities, combat market uncertainty, and sustain a competitive advantage. As a result, vendors have moved beyond core data analysis, visualization, and reporting capabilities and have shifted focus toward no and low-code data science, analytics automation, and data engineering. When projecting adoption throughout the next year, Nucleus expects customers to prioritize a solution’s broader support for data preparation, management, and data science, especially capabilities geared toward non-technical users, enabling organizations to scale their analytics and data science workloads without expanding technical headcount.