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What is Salford Predictive Modeler (SPM)?

The Salford Predictive Modeler® (SPM) software suite is renowned for its remarkable speed and accuracy in crafting predictive, descriptive, or analytical models. Featuring engines such as CART®, TreeNet®, and Random Forests®, along with innovative automation capabilities and unique modeling functionalities, SPM stands out in the realm of data analysis tools. This comprehensive suite encompasses a range of data mining technologies, including classification, regression, survival analysis, and methods for handling missing values, as well as data binning and clustering. SPM algorithms are invaluable in sophisticated data science applications, making them a cornerstone for analysts seeking to derive insights from complex datasets. The automation of model construction is significantly streamlined with SPM, facilitating a more efficient exploration and refinement process. Furthermore, the suite allows for the seamless integration of results from various modeling approaches into a single, cohesive package, enhancing the review process for users. This combination of features not only boosts productivity but also empowers data professionals to make informed decisions more effectively.

What is Continual?

Effortlessly create continuously evolving predictive models without the complexities of detailed engineering procedures. Integrate smoothly with your existing cloud data warehouse, making full use of all available data stored in its current location. Share features and deploy sophisticated machine learning models easily by utilizing just SQL or dbt, with the option to enhance capabilities using Python when necessary. Keep predictions neatly organized in your data warehouse to ensure easy access for both your business intelligence and operational systems. Manage features and predictions right within your data warehouse, which removes the need for any extra infrastructure. Build state-of-the-art models that leverage all your data without having to write code or set up complex pipelines. Encourage collaboration between analytics and AI teams thanks to the extensive flexibility offered by Continual's declarative AI framework. As your operations scale, monitor features, models, and policies through a declarative GitOps workflow. Accelerate the model development process with a collaborative feature store and a data-driven approach, while also ensuring smooth communication across teams. This forward-thinking strategy not only streamlines workflows but also promotes a more cohesive environment for deriving insights and achieving successful outcomes. Ultimately, this leads to a more agile response to business needs and an enhanced capacity for innovation.

Media

Media

Integrations Supported

Integrations Supported

Amazon Redshift
Databricks
Google Cloud BigQuery
Snowflake

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Minitab

Date Founded

1972

Company Location

United States

Company Website

www.minitab.com/en-us/products/spm/

Company Facts

Organization Name

Continual

Date Founded

2019

Company Location

United States

Company Website

continual.ai/

Categories and Features

Data Mining

Predictive Modeling

Machine Learning

Not specified

Predictive Analytics

Not specified

Categories and Features

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