Critical Capabilities for Data Science and Machine Learning Platforms

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400-1According to Gartner, end user organizations report that a significant number of data science projects involve four major use cases: business exploration, advanced prototyping, production refinement, and augmented data science and machine learning.

Get a copy of the report "2020 Critical Capabilities for Data Science and Machine Learning Platforms," compliments of Dataiku, to discover key platform features to consider as well as why Dataiku scored highest in two of the four use cases.

Read on for more information on Dataiku, the platform democratizing access to data and enabling enterprises to build their own path to AI, including robust model monitoring systems.

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INCLUSIVE

Dataiku provides one simple UI for data wrangling, mining, visualization, machine learning, and deployment based on a collaborative and team-based user interface accessible to anyone on a data team, from data scientist to beginner analyst.

Dataiku also offers a visual AutoML suite that guides the user through all of the machine learning steps (train-test split, features handling, metrics to optimize, different templates of pre-set algorithms).

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PREVALENT

The transformation to AI must be global within the organization and not just to focus on a specific niche. Dataiku provides support of hybrid deployment models (including operationalization and self-service analytics) plus the ability to elastically scale to match data location and cost constraints.

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RESPONSIBLE

No matter what the underlying changes in architecture or advancements in technology, Dataiku is at the center, providing a path to AI that is:

  • Accountable: Ensuring that models are designed and behave in ways aligned with their purpose.
  • Sustainable: Establishing the continued reliability of AI-augmented processes in their operation as well as execution.
  • Governable: Centrally controlling, managing, and auditing the Enterprise AI effort.

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Gartner, Critical Capabilities for Data Science and Machine Learning Platforms, 2 March 2020, Pieter den Hamer, Peter Krensky, Alexander Linden, Carlie Idoine, Erick Brethenoux, Jim Hare, Svetlana Sicular, Farhan Choudhary. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and is used herein with permission. All rights reserved. This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Dataiku. Gartner does not endorse any vendor, product, or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.