Published: 24 June 2024
Core data science is a practice centered on providing insight-driven decision making for improving business outcomes. Data and analytics leaders should use this set of critical capabilities for data science and machine learning platforms to govern, scale and maximize this practice.
Data science and machine learning (DSML) platforms continue to democratize the usage of DSML techniques beyond purely code-driven development through GenAI-driven assistive features for data wrangling and automated insight generation.
Expert data science teams also benefit from GenAI-based code assistance for model development in notebook environments and the ability to deliver interactive chat-based applications for end users.
The need for collaboration between multidisciplinary technical and business teams is being addressed through workflow management, conversion between low-code and code-based models, and documentation generation.
Redesign DSML operating models to take into account the augmented features of DSML platforms to decentralize more development
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Analysts:
Aura Popa, Tong Zhang, Afraz Jaffri, Peter Krensky, Raghvender Bhati, Jim Hare, Maryam Hassanlou
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