Domino Data Science Blog

Today's most successful organizations put AI and machine learning models at the heart of their business, creating competitive advantage by accelerating innovation, improving customer experience, and making faster and less-biased decisions. Data science teams building AI-driven applications and experiences require flexible access to the latest tools and any data across hybrid, multi-cloud and on-premises environments. Success with building models that drive digital transformation also requires the security, governance, and compliance that enterprises and governments expect regardless of the underlying infrastructure.

Building a great machine learning model often starts with getting access to critical data – about patients in clinical trials, loans that have defaulted, transactions at individual stores, etc. Despite the hype around creating a “data lake” where all of a company’s data will reside, the reality for most companies is that data is often in a variety of different locations, both on-premises and in the cloud. And, the number of these locations grows quickly within larger organizations, with many different departments, different needs, and different storage requirements.

Over the last five years, data science has become significantly more complex:

By Bob Laurent, Sr. Director of Product Marketing, Domino on June 21, 2021 in Product Updates

Forrester recently surveyed¹ thousands of business and technology decision-makers to gain insight into their use of data and analytics, and the factors that contribute to their purchasing decisions. When asked what benefits their organization expected when using Artificial Intelligence (AI) technologies: