Don’t Get Left Behind in the AI Race: Your Easy Starting Point is Here
Enterprise organizations with outdated, on-premises data analytics infrastructure face frustrations related to scaling up and down this infrastructure and the software that runs on it as data demands fluctuate over time. Given the inelasticity of an on-premises data analytics architecture, scaling becomes both costly and time-consuming, delaying the time-to-value of strategic data analytics projects and increasing pressure on IT and business teams to deliver value from analytics.

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