Democratizing Data Science

Create a scalable framework for your AI and Machine Learning initiatives

Although the amount of data organizations are generating today is increasing, R&D productivity has steadily declined. Outside of the costs of carrying out R&D, external factors such as disjointed IT environments and increasing regulatory pressure are exacerbating the issue. Many are turning to data science initiatives, yet the talent pool often lacks the discipline-specific knowledge needed for success. 

The whitepaper, "Creating a Scalable Framework for Data Science," covers the best practices organizations can take to maximize the value of their existing data science resources or optimize their plan for bringing in talent. Read the white paper to learn more.

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