What are the features included in Named User

Products	Versions
Spotfire Statistica	14.0 and higher

Description

TIBCO Data Scientist is sold as Named User or customers can purchase add-ons to TIBCO Statistica® Data Scientist for a metadata store, job server, versioning/approval, monitoring & alerting, live scoring, manual data entry & analytics and interactive dashboards. If an add-on is purchased, then TIBCO Statistica™ Data Scientist includes a license server. The license server is also included if concurrent user licensing is purchased.

Issue/Introduction

This article provides the features included in TIBCO Data Scientist.

Environment

Windows operating systems only.

Resolution

The product contains the following features:

automation for data cleaning; dirty data is the most common analytics problem
business rules builder
exploratory analysis & visualizations; learn about the problem space
descriptive statistics, nonparmetrics; 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 experiements
tabulation options; everyone needs a summary table for their presentation to management

There are two modes of interaction with the 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 lables, missing data, outliers, etc.. on every variable. The results of this analyses is a diagnostic report. This node can also be configured to automate fix the data problems uncovered by the analyses.

Additional options to transform and clean are available; feature selection (select the best predictors), remove duplicates, recode, rank, merge, process invariant variables, recode outliers, missing data inputation, recode missing data, subset, sample, filtering (variable 1 = "X"), crosstable (also known as pivot), 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 and low-code tool that:

documents the analytic steps
imports excel, csv, fixed width (mainframe) data
embed sdata 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.

PI Connector

The PI Server is a real-time data storage and distribution engine that powers the PI System (http://www.osisoft.com). Statistica has a PI Connector to retrieve data from this system for analysis. In 2015 OSIsoft announced that the PI SDK is transitioning to deprecation. And the vendor recommended users start transiting to the replacement product; PI AF (asset framework). Statistica will continue to support PI SDK until the vendor ends the product. PI AF connector is available.