These providers have recently been named major players in data science and machine learning platforms for 2021 by analyst house Gartner, Inc.
Data science and machine learning platforms come in a variety of shapes and sizes to meet the ever-changing needs of organizations and their increasingly complex environments. Enterprises require solutions that can serve a number of different use cases like data discovery, visualization and insight generation. There are both small and large providers that offer software to help these companies with both niche and common challenges, though choosing the vendor(s) that are right for your specific environment can be a daunting task.
The following providers have recently been named leaders in the 2020 Gartner Magic Quadrant for Data Science and Machine Learning Platforms. The report, which highlights and scores the top products in the industry, features these four tools as being cornerstones in the space. Each provider’s market share and product portfolios differ, which is what makes them interesting to the wider audience of data consumers. Niche and emerging vendors can only hope to replicate the kind of market presence that these providers have earned over a sustained period of time. Here we provide a brief blurb about each and links to product details so you can learn more.
SAS offers a strong suite of advanced analytics and data science products. Its SAS Platform provides access to data in any format and from any source, automated data preparation, and data lineage and model management. SAS Visual Data Mining and Machine Learning automatically generates insights for common variables across models. It also features natural language generation for creating project summaries. SAS Model Manager enables users to register SAS and open source models within projects or as standalone models.
IBM Watson Studio enables users to build, run, and manage AI models at scale across any cloud. The product is a part of IBM Cloud Pak for Data, the company’s main data and AI platform. The solution lets you automate AI lifecycle management, govern and secure open-source notebooks, prepare and build models visually, deploy and run models through one-click integration, and manage and monitor models with explainable AI. IBM Watson Studio offers a flexible architecture that allows users to utilize open-source frameworks like PyTorch, TensorFlow, and scikit-learn.
Dataiku offers an advanced analytics solution that allows organizations to create their own data tools. The company’s flagship product features a team-based user interface for both data analysts and data scientists. Dataiku’s unified framework for development and deployment provides immediate access to all the features needed to design data tools from scratch. Users can then apply machine learning and data science techniques to build and deploy predictive data flows.
TIBCO offers an expansive product portfolio for modern BI, descriptive and predictive analytics, and streaming analytics and data science. TIBCO Data Science lets users do data preparation, model building, deployment and monitoring. It also features AutoML, drag-and-drop workflows, and embedded Jupyter Notebooks for sharing reusable modules. Users can run workflows on TIBCO’s Spotfire Analytics and leverage TensorFlow, SageMaker, Rekognition and Cognitive Services to orchestrate open source.
Databricks offers a cloud and Apache Spark-based unified analytics platform that combines data engineering and data science functionality. The product leverages an array of open source languages, and includes proprietary features for operationalization, performance and real-time enablement on Amazon Web Services. A Data Science Workspace enables users to explore data and build models collaboratively. It also provides one-click access to preconfigured ML environments for augmented machine learning with popular frameworks.
MathWorks MATLAB combines a desktop environment tuned for iterative analysis and design processes with a programming language that expresses matrix and array mathematics directly. It includes the Live Editor for creating scripts that combine code, output, and formatted text in an executable notebook. MATLAB toolboxes are professionally developed, tested, and fully documented. MATLAB apps let you see how different algorithms work with your data as well.