Gartner’s 2021 Magic Quadrant cites ‘glut of innovation’ in data science and ML | VentureBeat

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Gartner’s Magic Quadrant report on data science and machine learning (DSLM) platform companies assesses what it says are the top 20 vendors in this fast-growing industry segment.

Data scientists and other technical users rely on these platforms to source data, build models, and use machine learning at a time when building machine learning applications is increasingly becoming a way for companies to differentiate themselves.

Gartner says AI is still “overhyped” but notes that the COVID-19 pandemic has made investments in DSLM more practical. Companies should focus on developing new use cases and applications for DSML — the ones that are visible and deliver business value, Gartner said in the report released last week. Smart companies should build on successful early projects and scale them.

The report evaluates DSML platforms’ scope, revenue and growth, customer counts, market traction, and product capability scoring. Here are some of the notable findings:

There remains a “glut of compelling innovations” and visionary roadmaps, Gartner says. This is an adolescent market, where vendors are heavily focused on innovation and differentiation, rather than pure execution. Gartner said key areas of differentiation include UI, augmented DSML (AutoML), MLOps, performance and scalability, hybrid and multicloud support, XAI, and cutting-edge use cases and techniques (such as deep learning, large-scale IoT, and reinforcement learning).

Above: Gartner Magic Quadrant for Data Science and Machine Learning Platforms. (Source: Gartner, March 2021)

Data science and machine learning in 2021 and beyond

For most enterprises, the challenge is to keep up with the rapid pace of change in their industries, driven by how fast their competitors, suppliers, and channel partners are digitally transforming their businesses.

Which vendors are leading — and why

Here are some company-specific insights included in this year’s Magic Quadrant:

The challenges for DSML platform vendors today begin with balancing the needs for greater transparency and bias mitigation while developing and delivering innovative new features at a predictable cadence. The Magic Quadrant reflects current market reality after updating with four new cloud vendors, one with an extensive ecosystem and proven market momentum.

One thing to consider after looking at the Magic Quadrant is that there will be some mergers or acquisitions on the horizon. Look for BI vendors to either acquire or merge with DSML platform providers as the BI market’s direction moves toward augmented analytics and away from visualization. Further fueling potential M&A activity is the fact that DSML platforms could use enhanced data transformation and discovery support at the model level, which is a long-standing strength of BI platforms.

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