Leaders Despite Challenges: 2024 Gartner® Magic Quadrant™ for Data Science and Machine Learning Platforms

Gartner recently released a comprehensive report on Data Science and Machine Learning platforms, highlighting Databricks as a leader. Notably, the report also reveals that many vendors share common challenges, which can be grouped into several categories:

Complexity/usability

This category encompasses challenges related to the complexity and usability of the platforms, which can hinder user experience and productivity. These challenges include:

• technical complexity

• usability issues

• performance tuning

• navigation and management

50% of the vendors are affected, including Alibaba Cloud, AWS, Cloudera, Databricks, Domino Data Lab, MathWorks, Microsoft, Posit, and KNIME.

Product integration/coherence

This category includes challenges related to integrating various product components and maintaining coherence across products. Key points include:

• legacy systems

• component overlap

• vision development

• design considerations

44% of vendors are affected, including Altair, Alteryx, AWS, Cloudera, Databricks, IBM, H2O.ai, and KNIME.

Target audience/specialization

This category highlights limitations in addressing the needs of specific user groups. Vendors may focus too narrowly on certain user types, leading to:

• underserved user groups

• focus on non-experts

• specialization issues

33% of the vendors are affected, including Anaconda, Alteryx, Domino Data Lab, MathWorks, KNIME, and Posit.

Innovation/feature gaps

This category pertains to gaps in innovative features and the ability to keep up with cutting-edge technologies. Vendors may:

• lag in GenAI capabilities

• miss out on functionalities

• develop features slowly

28% of vendors are affected, including AWS, Google, MathWorks, SAS, and Posit.

Although Databricks is present in two categories - Complexity/usability and Product integration/coherence - due to performance tuning, cluster management issues, and alignment challenges with hybrid architectures, these did not prevent it from becoming the leader of the Magic Quadrant in 2024.

Source: Magic Quadrant for Data Science and Machine Learning Platforms

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