Multimodal PAML — or predictive analytics and machine learning — solutions reimagine how data science teams work, Forrester says, delivering its report “The Forrester Wave: Multimodal Predictive Analytics And Machine Learning Solutions, Q3 2018” this week.
Machine learning has been increasingly important in transforming enterprise applications across all industries because it delivers the power to predict, to learn from data and find hidden insights. It can give huge enterprises the agility of disruptive upstarts, and cloud providers enable the smallest of businesses with equal access to computational power.
While artificial intelligence, of which machine learning is a subset, is not new, it has only become largely viable to many in recent years, through advances in cloud computing. However, what is not new is the sound analytical foundation that underpins machine learning, and this necessitates a mature, sophisticated product that aids data scientists and associated professionals in their enterprise predictive analytics and machine learning (PAML) solutions.
For the research, PAML products have been defined as software that provides
- Tools to analyse data;
- Workbench tools to build predictive models using statistical and ML algorithms;
- A platform to train, deploy and manage analytical results and models; and
- Collaboration tools for extended enterprise teams.
Forrester identified three leading products – RapidMiner for its easy-to-use visual environment, IBM Watson Studio for its mix of visual tools and open source libraries, and SAS for its powerful unified platform.
In fact, it is SAS which was rated best by Forrester, with the research firm stating, “SAS builds the first truly multimodal PAML solution.”
By multimodal, Forrester means SAS provides the widest breadth of workbench tools, as well as tools for non-data scientists to build pipelines and models and collaborate with data scientists.
The report evaluated SAS Visual Data Mining and Machine Learning, which runs on the SAS Viya engine and includes the latest statistical, machine learning, deep learning and text analysis algorithms that accelerate structured and unstructured data explorations, while also supporting popular open source languages.
“Highly skilled data scientists and analytical professionals are in short supply as organisations struggle to find solutions to complex business problems,” said Lorry Hardt, artificial intelligence and machine learning strategist at SAS.
“Built for speed and simplicity, SAS machine learning tools address all of the steps necessary for data scientists to business users alike to turn raw data into actionable insights. Since machine learning is a cornerstone technology for artificial intelligence, this SAS expertise is particularly valuable as more and more organisations embrace the power and the promise of AI.”