3 Steps for Better Data Modeling With IT, Data Scientists and Business Analysts Your email has been sent Data analysts can help build accessible and effective data models by defining business ...

Data scientists and data engineers are both critical roles for data-driven organizations. When they work well together, it can be magical. But too often, their relationships are fraught with tension ...

With so much attention devoted to the purported wonders of predictive cognitive computing models (typically characterized by classic machine learning and deep learning), it’s easy to lose sight of the ...

I recently moderated a webinar roundtable on behalf of Domino Data Lab called “Unleash Data Science for the Model-Driven Business You Expect.” I don’t know that everyone expects a model-driven ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

Data science can make robotic process automation more intelligent. Robotic process automation make it easier to deploy data science models in production. Robotic process automation (RPA) companies are ...

Data Science is a structured approach to extracting valuable insights from data, and it involves several key stages to ensure success. Let's explore each phase in detail: By following this structured ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

The Data Science and Modeling for Green Chemistry award aims to recognize the research and development of computational tools that guide the design of sustainable chemical processes and the execution ...