Customers can purchase add-ons to Spotfire Statistica® Modeler for a metadata store, job server for scheduling, versioning/approval, monitoring & alerting service, live scoring, manual data entry, and interactive dashboards. If an add-on is purchased, then Spotfire Statistica® Modeler includes a license server. The license server is also included if concurrent user licensing is purchased.
Spotfire Statistica® Modeler contains the following features:
- automation for data cleaning; dirty data is the most common analytics problem
- Spotfire Statistica® Rules Builder
- exploratory analysis & visualizations; learn about the problem space
- descriptive statistics, nonparametric; learn and share factoids about the problem to build situational awareness
- linear regression models, nonlinear regression models; estimate the relationships among your variables and create predictive models (machine learning); also use simulated data to create linear regression models and learn something new
- multivariate exploratory techniques; organize data into meaningful clusters, classify variables (reduce/relate variables), principal components & classification analysis
- process analysis, quality control, multivariate statistical process control; understand critical process parameters which impact critical quality attributes
- design of experiments, power analysis, and interval estimation; experiment and discover; also use simulated data to execute virtual experiments
- tabulation options; everyone needs a summary table for their presentation to management
There are two modes of interaction with analytics; spreadsheet and workspace. For ad-hoc analysis that does not need to be duplicated, users can import data into a spreadsheet and interact with menus, variables, and rows of data. The workspace is a visual analytic workflow management tool and is recommended. This allows work to be saved and reused. No coding is needed to complete a workspace. And for the users who need to manage their code, the workspace has a "code node" which can execute C#, Python, or R code.
Data Profiling, Cleaning, Transformation
The Data Health Check node (data profiling) explores values, value ranges, discrete text labels, missing data, outliers, etc.. on every variable. The result of this analysis is a diagnostic report. This node can also be configured to automate and fix the data problems uncovered by the analyses.
Additional options to transform and clean are available; remove duplicates, recode, rank, merge, process invariant variables, recode outliers, missing data imputation, recode missing data, subset, sample, etc.
Box-Cox is available to transform variables so that they have a distribution as close to normality as possible (Box and Cox, 1964). This allows the use of algorithms, like regression analysis, that only work with a normal distribution.
Workspace Features
A workspace is a no-code tool that:
- documents the analytic steps
- imports excel, csv, fixed width (mainframe) data
- embeds data within workspace as a lookup table; transform "m" to Monday for readability
- imports Spotfire SBDF data file and configure analytics (see options below)
- retrieves data from database with ODBC driver and configure analytics (see options below)
- creates data mashup
- creates visualizations
- formats output for reporting
- exports results to excel, csv, Spotfire SBDF, etc.
- writes results into a database; SQL Server, Oracle, Teradata, SQL Server PDW, PostgreSQL, DB2
- workspace calls another workspace
The workspace can also be extended with R, C#, or Python coding.
Visualizations
2D and 3D visualizations are available with the product; histogram, line, scatterplot, means with error, bag plots, quantile-quantile (beta, exponential, extreme, gamma, lognormal, normal, Rayleigh, Weibull), variability, contour, wafer, normal probability, etc. Interactive dashboards are available for the analytic user.
Analytics
- Spotfire Statistica® ANOVA MANOVA
- Spotfire Statistica® Association Rules
- Spotfire Statistica® Automated Neural Networks
- Spotfire Statistica® Boosted Tree
- Spotfire Statistica® Calculators (Distributions, Pearson Product Moment Correlation Coefficient, Six Sigma)
- Spotfire Statistica® Canonical Analysis
- Spotfire Statistica® Classification Trees
- Spotfire Statistica® Cluster Analysis
- Spotfire Statistica® Correlation
- Spotfire Statistica® Correspondence Analysis
- Spotfire Statistica® Cox Proportional Hazards Models
- Data Miner Recipes
- Spotfire Statistica® Descriptive Statistics
- Spotfire Statistica® Design of Experiments (DOE)
- Spotfire Statistica® Discriminant Function Analysis
- Spotfire Statistica® Distribution Fitting
- Spotfire Statistica® Distributions & Simulation
- Spotfire Statistica® Dynamic Time Warping
- Spotfire Statistica® Factor Analysis
- Faster Independent Component Analysis
- Feature Selection
- Spotfire Statistica® Fixed Nonlinear Regression
- General CHAID Models
- General Classification and Regression Trees (C&RT)
- Spotfire Statistica® General Discriminant Analysis (GDA)
- Spotfire Statistica® General Linear Models (GLM)
- Spotfire Statistica® General Partial Least Squares Models (PLS)
- Spotfire Statistica® General Regression Models (GRM)
- Generalized Additive Models (GAM)
- Spotfire Statistica® Generalized Linear Nonlinear Models (GLZ)
- Goodness of Fit, Classification, Prediction
- Independent Component Analysis
- Interactive Tree (C&RT, CHAID)
- Lasso Regression
- Link Analysis
- Spotfire Statistica® Log-Linear Analysis of Frequency Tables
- Machine Learning (Bayesian, Support Vectors, K-Nearest)
- Spotfire Statistica® Multidimensional Scaling (MDS)
- Multivariate Adaptive Regression Splines (MARSplines)
- Spotfire Statistica® Multiple Regression
- Network analytics
- Spotfire Statistica® Nonlinear Estimation
- Spotfire Statistica® Nonparametric Statistics
- Spotfire Statistica® Power Analysis and Interval Estimation
- Spotfire Statistica® Multivariate Statistical Process Control (MSPC - PCA / PLS)
- Optimal Binning
- Predictor Screening
- Spotfire Statistica® Principal Components & Classification Analysis (PCCA)
- Spotfire Statistica® Process Analysis
- Spotfire Statistica® Quality Control Charts
- Random Forests
- Rapid Deployment of Predictive Models (PMML)
- Reliability and Item Analysis
- Sequence and Link Analysis
- Spotfire Statistica® Stepwise Model Builder (what-if)
- Spotfire Statistica® Structural Equation Modeling and Path Analysis (SEPATH)
- Spotfire Statistica® Survival & Failure Time Analysis
- Spotfire Statistica® Time Series Forecasting
- Spotfire Statistica® T-Tests And Other Tests Of Group Differences
- Spotfire Statistica® Tabulate
- Spotfire Statistica® Variance Components & Mixed Model ANOVA ANOCOVA
- Weight of Evidence
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