Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Organizations allocate substantial budgets each year to manage extensive cloud data, yet they typically utilize only a small portion for forecasting purposes. Kumo empowers these companies to tap into the complete capabilities of their enterprise data, facilitating quicker, more straightforward, and more intelligent predictions. While traditional SQL queries focus on historical data, Kumo allows users to explore future possibilities. Standard enterprise AI approaches often treat each predictive analysis in isolation. In contrast, enterprise data is a vibrant, interconnected network of business relationships, customer interactions, transactions, and beyond. By harnessing the interconnectivity of this data, Kumo fosters a significant advancement in AI technology. Its cutting-edge graph learning capabilities yield significantly improved accuracy, even with substantially less training data. Transition effortlessly from raw data at the storage level to producing reliable predictions over time. Remarkably, Kumo can analyze extensive databases in mere minutes rather than the usual hours or days, enhancing efficiency in data-driven decision-making. This innovation not only streamlines the prediction process but also empowers businesses to leverage their data like never before.
Description
The Salford Predictive Modeler® (SPM), software suite, is highly accurate and extremely fast for developing predictive, descriptive, or analytical models. Salford Predictive Modeler®, which includes the CART®, TreeNet®, Random Forests® engines, and powerful new automation capabilities and modeling capabilities that are not available elsewhere, is a software suite that includes the MARS®, CART®, TreeNet[r], and TreeNet®. The SPM software suite's data mining technologies span classification, regression, survival analysis, missing value analysis, data binning and clustering/segmentation. SPM algorithms are essential in advanced data science circles. Automation of model building is made easier by the SPM software suite. It automates significant portions of the model exploration, refinement, and refinement process for analysts. We combine all results from different modeling strategies into one package for easy review.
API Access
Has API
No
API Access
Has API
No
Integrations
Snowflake Cortex AI
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Kumo
Country
United States
Website
kumo.ai/
Vendor Details
Company Name
Minitab
Founded
1972
Country
United States
Website
www.minitab.com/en-us/products/spm/
Product Features
Predictive Analytics
AI / Machine Learning
No
Benchmarking
No
Data Blending
No
Data Mining
No
Demand Forecasting
No
For Education
No
For Healthcare
No
Modeling & Simulation
No
Sentiment Analysis
No
Product Features
Data Mining
Data Extraction
No
Data Visualization
No
Fraud Detection
No
Linked Data Management
No
Machine Learning
No
Predictive Modeling
Yes
Semantic Search
No
Statistical Analysis
No
Text Mining
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Predictive Analytics
AI / Machine Learning
No
Benchmarking
No
Data Blending
No
Data Mining
No
Demand Forecasting
No
For Education
No
For Healthcare
No
Modeling & Simulation
No
Sentiment Analysis
No