About XLMiner for the Web

Data mining, text mining, forecasting, and predictive analytics with point-and-click ease in your browser.

XLMiner is a cloud-based service offered with three different subscription plans: XLMiner Education (free), XLMiner Pro, and XLMiner Platform. All the features described here are available in all three plans, but with different size limits on datasets, and limits on CPU time used.

Easy to use interface Use a Ribbon, simple dropdown menus, and Wizard-style dialogs to guide you through model and option selections. View results through a spreadsheet-like grid display.
Use data from many sources Sample data from uploaded spreadsheets and CSV files, SQL databases (including our sample Azure SQL database), and Big Data (including our Apache Spark cluster on Amazon Web Services).
Analyze text for insights Automatically transform free-form text into structured data, identifying most frequent terms and extracting key concepts with latent semantic indexing.
Clean & transform data Clean and transform your data with a comprehensive set of data handling utilities including categorizing data and handling missing values.
Identify key features Use feature selection to automatically identify columns or variables with the greatest explanatory power for your desired classification or prediction task.
Reduce and cluster data Use principal components to reduce columns, and k-means clustering or hierarchical clustering to group data by rows.
Partition for training Easily partition your data into training, validation, and test datasets, with no limits on dataset size -- even "on the fly" as you build a predictive model.
Forecast time series Apply the most popular exponential smoothing and Box-Jenkins (ARIMA) methods with seasonality to forecast time series, such as sales and inventory, from historical data.
Prediction methods Use powerful multiple linear regression with variable selection, and data mining methods like k-nearest neighbors, and ensembles of regression trees and neural networks.
Classification methods Use classical discriminant analysis and logistic regression, and data mining methods like k-nearest neighbors, naive Bayes, and ensembles of classification trees and neural networks.
Affinity analysis Use market basket analyses and recommender systems with association rules.
Example datasets Example datasets give you practice with a range of prediction, classification, time series forecasting, and affinity analysis problems.
Help and support Access extensive online Help, or review our 400+ page XLMiner User Guide to get your questions answered.
Compatibility with Excel Everything you learn in XLMiner for the Web can also be applied in XLMiner for Excel.

XLMiner may be easy to use, but don't underestimate its enterprise-grade power. Your data is analyzed by state-of-the-art data mining and text mining algorithms, running on scalable Azure cloud services -- part of our RASON® Analytics Server.