Published: 13 March 2021
The functions and features of data science and machine learning platforms are evolving quickly to keep pace with a highly innovative space. This research helps data and analytics leaders to evaluate 20 of these platforms across 15 critical capabilities.
Business and data exploration are an integral part of many platforms, offering a common ground for the vital collaboration between (citizen) data scientists and domain experts.
Citizen data science is now supported by a majority of vendors, bringing the power of machine learning within reach of nonexperts.
Expert model development often requires cutting-edge (open-source) techniques, for which many vendor platforms offer first-class support.
Operationalization is more critical than ever as organizations seek to scale their data science and machine learning, demanding tangible business value from projects.
Data and analytics leaders tasked with incorporating data science and machine learning into their analytics strategies
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As a companion to the Magic Quadrant™, a Critical Capabilities report scores competing products and services against a set of meaningful differentiators. It reveals which options are the best fit in various use cases to help you focus on the vendors best suited to your needs.
Narrow down the product and service criteria most important to you.
Use interactive features to customize usage scenarios based on your organization’s unique needs.
Use data to speed up provider selection and accelerate the procurement process.
We provide actionable, objective insight to help organizations make smarter, faster technology decisions to stay ahead of disruption and accelerate growth.
We use a Critical Capabilities report, the Magic Quadrant and more to ensure you select the best-fit provider to avoid the costly repercussions of a poor decision.
We benchmark pricing against the market so you avoid unnecessary charges.
We analyze contract terms and conditions to protect you against future price increases and unanticipated costs.
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