STATISTICA Data Mining, Text Mining and Predictive Analytics Software

Data Mining is the differentiator. Some have labelled the current period, appropriately, as
“The Age of Analytics,” a period in which the information age has led us to the application of
analytics to derive insights from these incredible sources of data. 

At StatSoft, we have the opportunity to collaborate with, consult, and train colleagues in the areas of data analysis and predictive modelling in a variety of industries: automotive manufacturing, financial services, medical device manufacturing, pharmaceutical R&D and manufacturing, semiconductors, etc. What our experience has taught us is that, in a competitive economy, companies can focus on opportunities for utilizing advantages and streamlining. One category of opportunity is to leverage the data that your company has already collected and manages.

Software

The STATISTICA Data Analysis and Data Mining Platform, including the STATISTICA Data Miner software, offers the most comprehensive and effective system of user-friendly tools for the entire data mining process – from querying databases to generating final reports. StatSoft’s data mining and predictive modelling software is available in single workstation, multiple-user (concurrent user licensing), and Enterprise editions.

STATISTICA Text Miner is an optional extension of STATISTICA Data Miner, ideal for translating unstructured text data into meaningful information.

The Enterprise edition provides an efficient server-platform, for off-loading resource-intensive model-building tasks, Web browser-based or Windows workstation clients, and central configurations of queries, analyses, report templates, and models.

STATISTICA Scorecard aids the development, evaluation and monitoring of scorecard models,STATISTICA Live Score is STATISTICA Server software within the STATISTICA Data Analysis and Data Mining Platform. Data are aggregated and cleaned and models are trained and validated using the STATISTICA Data Miner software. Once the models are validated, they are deployed to the STATISTICA Live Score server. STATISTICA Live Score provides multi-threaded, efficient, and platform-independent scoring of data from line-of-business applications.

STATISTICA Process Optimization, an optional extension of STATISTICA Data Miner, is a powerful software solution designed to monitor processes and identify and anticipate problems related to quality control and improvement with unmatched sensitivity and effectiveness.

Services (Consulting, Training)

StatSoft’s Professional Services offer data mining consulting and training. StatSoft offers an efficient ‘Quick Start’ package of training and consulting as an optional addition to the licensing of the STATISTICA Data Miner software, assisting new software users with delivering business value and return-on-investment as quickly as possible after the acquisition of the software. StatSoft’s consultants take a collaborative approach to projects, mapping the scope of services to fit your business priorities and available resources.

Information about Data Mining Methods

Below are useful links to StatSoft’s overviews of popular data mining methods provided in the STATISTICA Data Miner platform:

Association Rules
Classification and Regression Trees
CHAID
Boosting Trees
Cluster Analysis
Support Vector Machines
MARSplines
Naïve Bayesian Classifiers
Text Mining
Partial Least Squares
Independent Components Analysis

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About statsoftsa

StatSoft, Inc. was founded in 1984 and is now one of the largest global providers of analytic software worldwide. StatSoft is also the largest manufacturer of enterprise-wide quality control and improvement software systems in the world, and the only company capable of supporting its QC products worldwide, with wholly owned subsidiaries in all major markets (StatSoft has 23 full-service offices, on all continents), and its software is available in more than 10 languages.

Posted on May 24, 2011, in Data Miner, Product Information, Statistica and tagged , , , , , , , , , , , , , . Bookmark the permalink. Leave a comment.

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