Here’s why IDC MarketScape named IBM a leader in advanced machine learning software

By | 2 minute read | December 11, 2020

Insights driven organizations are disrupting their industries by harnessing the power of Artificial Intelligence (AI) and Machine Learning (ML) models to accelerate digital transformation. They realize that time to value is critical because in a dynamic business environment, insights can be rendered stale if they are not timely. In such a scenario, organizations must  streamline the process of building, testing and deploying AI and ML models .

The successful organizations are the those able to tap into the collective wisdom of cross-functional team members including business users, analysts, data scientists, application developers and SMEs to improve efficacy of their data science practices. They do this by simplifying data access, democratizing the use of data science tools  and techniques,  and adopting sound ModelOps practices to ensure that the  models can be easily deployed and managed in production.

IBM Watson Studio Premium for Cloud Pak for Data has enabled several organizations capitalize on the transformative power of data science to  automate, predict and optimize business outcomes. What sets IBM apart is the ability to deploy AI and ML models anywhere, depending on your organization’s need for deploying  models on multiple pubic clouds, private cloud and on premises behind your firewall.

This is validated by the  2020 IDC MarketScape for Worldwide Advanced Machine Learning Software Platforms where IBM is positioned in the Leaders category. 

What are advanced machine learning platforms

Advanced machine learning platforms provide a range of ML methods primarily working with structured and semi-structured data to create predictive and prescriptive models that are then used in applications. These platforms facilitate the development of advanced machine learning models and applications. Advanced machine learning platforms can also include development, training, and deployment tools, including pretrained models and automatic machine learning methods that help developers and business users to experiment, automate machine learning, and build and deploy artificial intelligence models into production

IBM Strengths as per the IDC MarketScape

IBM’s capabilities to automate model building with AutoAI and  simplify deployment of trusted AI was highlighted in the report. According to the IDC MarketScape report, “Watson Studio AutoAI significantly accelerates model creation and deployment by automating data preparation, model development, feature engineering, and hyper-parameter optimization, as well as offering one-click deployment through Watson Machine Learning (WML).”

The report highlights IBM’s decision optimization technology as one of the key differentiators within IBM Watson Studio. As per the IDC MarketScape’s evaluation, “Watson Studio also differentiates itself in the provision of prescriptive analytics capabilities for the design and deployment of optimization models. This enables business decision systems to use the output of predictive models in operational research (OR) scenarios. A natural language–based model builder allows OR experts as well as data scientists at any skill level to construct and solve optimization problems.”

The IDC MarketScape notes “With IBM Cloud Pak for Data running on Red Hat OpenShift, Watson tools and apps can be used on IBM Cloud, AWS, Azure, Google, or customers’ own private cloud using Kubernetes technology. It also has interoperability with an array of open source cloud-native, data, and AI capabilities.”

Learn more by downloading the IDC MarketScape for Worldwide Advanced Machine Learning Software Platforms today.

To learn how IBM Data science can help businesses drive innovation, watch our two-part webinar series on how to use IBM natural-language modelling interfaces to solve complex operational planning and scheduling.

Visit our website to learn more about the value of  IBM Watson Studio.

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