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Today’s businesses run on data, the volume of which is constantly and rapidly increasing. And organizations rely on more than traditional, transactional data; unstructured data has become just as critical. Legacy systems, while good at high-value workloads at a small or medium scale, are often not appropriate, as the volume, variability, and variety of data formats and requirements increase. Businesses that cannot cost-effectively innovate at these extremes of scale stand to lose out on opportunities to deeply engage with customers, optimize complex processes, and make better risk decisions. While many firms are pursuing opportunities, laggards are slowly realizing that their data architectures are collapsing under the weight of data they need to collect, store, and process. This study examines how US enterprise IT decision-makers are reacting to business data demands, what challenges they face in managing data, and why they are considering new technologies to pursue data innovation.

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