This node can also be configured to automate fix the data problems uncovered by the analyses.Īdditional options to transform and clean are available remove duplicates, recode, rank, merge, process invariant variables, recode outliers, missing data inputation, recode missing data, subset, sample, etc.īox-Cox is available to transform variables so that they have a distribution as close to normality as possible (Box and Cox, 1964). The results of this analyses is a diagnostic report. The Data Health Check node (data profiling) explores values, value ranges, discrete text lables, missing data, outliers, etc.
write results into a database SQL Server, Oracle, Teradata, SQL Server PDW, PostgreSQL, DB2įor 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.ĢD 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. 
export results to excel, csv, Spotfire SBDF, etc.
#Statsoft statistica descargar full driver#
retrieve data from database with ODBC driver and configure analytics (see options below).import Spotfire SBDF data file and configure analytics (see options below).embed data within workspace as a lookup table transform "m" to Monday for readability.import excel, csv, fixed width (mainframe) data.
And for the users who need to manage their code, the workspace has a "code node" which can execute C#, Python, or R code. No coding is needed to complete a workspace. The workspace is a visual analytic workflow management tool and is recommended. There are two modes of interaction with the analytics spreadsheet and workspace.
tabulation options everyone needs a summary table for their presentation to management. design of experiments, power analysis and interval estimation experiment and discover also use simulated data to execute virtual experiments. process analysis, quality control, multivariate statistical process control understand critical process parameters which impact critical quality attributes. multivariate exploratory techniques organize data into meaningful clusters, classify variables (reduce/relate variables), principal components & classification analysis. 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. descriptive statistics, nonparmetrics learn and share factoids about the problem to build situational awareness. exploratory analysis & visualizations learn about the problem space. automation for data cleaning dirty data is the most common analytics problem. It can generate Spotfire data files that TIBCO Spotfire® Desktop uses to create interactive dashboards. The TIBCO Statistica® Desktop product is sold for named user (i.e.
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