SAS Analytics Pro Features List

SAS Analytics Pro

and

SAS Analytics Pro Advanced Programming

Explore the Features of SAS Analytics Pro

Powerful 4GL with support for SQL

Ability to read data in nearly any format, from nearly any kind of file.
Robust macro language reduces coding for common tasks.
Centralized metadata repository.
Runs interactively or in batch mode.
PC/desktop version includes SAS Enterprise Guide for guided tasks and batch analysis.

Easily accessible browser-based development environment (SAS Studio)

Access SAS from anywhere, using any device with a web browser. No client installation. Zero footprint.
Access all of your SAS programs, data files and libraries from your desktop, Mac and iPad^® through your web browser.
Auto-complete feature displays a list of SAS procedures when you begin typing a procedure name. When a procedure is selected, it then displays the parameter list and pop-up syntax.
Automatically generates SQL queries and lets you access the SQL code generated behind the scenes.
Create and add your own code snippets to the snippet library.
Point-and-click interface guides you through analytical or data manipulation processes.
For more information, see Base SAS software.

Advanced statistical analysis

Examine data for relationships using a broad range of statistical methods, including:
- Analysis of variance.
- Bayesian analysis.
- Causal analysis.
- Categorical data analysis.
- Cluster analysis.
- Descriptive statistics.
- Discriminant analysis.
- Distribution analysis.
- Exact methods.
- Group sequential design and analysis.
- Market research.
- Mixed models.
- Missing value imputation.
- Multivariate analysis.
- Nonparametric analysis.
- Power and sample size.
- Psychometric analysis.
- Regression.
- Simulation and Monte Carlo methods.
- Spatial analysis.
- Structural equations.
- Survey sampling and analysis.
- Survival analysis.
- Transformations.
Multithreaded procedures.
Post-fitting inference.
Statistical graphics.
Ability to add drill-down capabilities so users can visually explore analyses.
For more information, see SAS/STAT. For a complete list of methods, see the SAS/STAT documentation.

Data visualization, preparation & delivery

Data visualization, presentation & delivery

Built-in map data sets (for countries, and US states and counties).
New map data sets from GfK have been added to the MAPS library. The MAPSGFK data is more current and cleaner topologically, for easier mapping and analysis.
Ability to generate latitude/longitude for mailing addresses and IP addresses.
Ability to analyze point data against data polygons to see where points are located.
Broad range of charts and plots:
- Scatter, line, area, bubble, multiple axis, overlay.
- Bar, pie, donut, star, block.
- Customized colors, line styles, symbols.
- 2-D and 3-D plots with tilting and rotation.
Customized colors, line styles and symbols.
Alpha transparency on charts.
Anti-aliased lines for smoother plot lines.
Generate static or dynamic interactive (Java or ActiveX) charts and graphs with drill-down capabilities.
Link graphs to web pages.
Embed interactive graphics in web pages or Microsoft documents.
Support for virtually all common printers and plotters.
Graphs are integrated with tables with all output displayed in the same HTML file.
For more information, see SAS/GRAPH.

Additional Capabilities Available With SAS Analytics Pro Advanced Programming

Model, forecast & simulate business processes for improved strategic & tactical planning

Model, forecast and simulate business processes for improved strategic and tactical planning by helping you to:
- Analyze the impact of promotions and events.
- Model customer choices and price elasticities.
- Model risk factors and predict economic outcomes.
- Make better staffing decisions.
- Forecast volatility and devise trading strategies.
Make better, more scientific decisions using methods covering a wide range of economic analysis and models:
- Autoregressive error models.
- Autoregressive integrated moving-average models.
- Bayesian analysis.
- Compound distribution modeling.
- Copula approach.
- Count regression.
- Discrete choice analysis.
- Error correction models.
- Exponential smoothing models.
- Limited dependent variable modeling.
- Linear Gaussian state space models.
- Long-memory time series.
- Panel data analysis.
- Polynomial distributed lagged models.
- Self-selection models.
- Severity of events modeling.
- Spatial econometric modeling.
- Stochastic frontier analysis.
- Systems modeling and simulation.
- Unobserved component models.
- Vector autoregressive moving-average models.
- Volatility forecasting with GARCH models.
Data management and preparation.
Specialized access to commercial and government databases.
Multithreaded procedures for high-performance econometrics.
For more information, see SAS/ETS.

Powerful, flexible matrix programming language

High-level matrix programming language enables you to program custom algorithms and implement new analytical methods.
Multithreaded matrix operations.
Linear algebra: support for popular operations and decompositions.
Data analysis: support for many classical and robust statistical methods.
Statistical graphics: support for common statistical graphics.
Numerical analysis: support for root-finding, integrals, derivatives, differential equations, interpolation and more.
Optimization: support for linear, mixed-integer, quadratic, and nonlinear programming problems, with or without constraints.
Simulation: support for simulating data from dozens of univariate and multivariate probability distributions, as well as implementing custom distributions.
For more information, see SAS IML. See the  SAS IML Language Reference for a complete list of methods.

Statistical process control software for improved product & process quality

Advanced quality control toolkit includes:
- Design of Experiments.
- Control Chart Analysis.
- Process Capability Analysis.
- Basic Quality Problem Solving.
- Reliability Analysis.
- Analysis of Means.
- Multivariate Process Monitoring.
Organize quality improvement efforts.
Design and analyze experiments for process discovery and optimization.
Apply Taguchi methods for quality engineering.
Establish statistical control of a process.
Maintain statistical control and reduce variation.
Assess process capability and analyze product reliability.
For more information, see SAS/QC Software. For a complete list of methods, see the  SAS/QC documentation.

Operations research software for identifying which actions will produce the best results, given constraints

The OPTMODEL family of procedures provides:
- Flexible algebraic syntax for intuitive model formulation.
- Transparent use of standard SAS functions.
- Direct invocation of linear, nonlinear, quadratic, network, and mixed-integer linear solvers.
- Support for the rapid prototyping of customized optimization algorithms, including named problems and subproblems.
- Ability to run other SAS code within PROC OPTMODEL with the SUBMIT block.
- Ability to execute solver invocations in parallel with the COFOR loop.
Linear programming algorithms:
- Primal simplex, dual simplex and network simplex.
- Interior-point with crossover.
Parallel branch-and-bound mixed-integer linear programming solver with cutting planes and primal heuristics.
Option tuning for mixed-integer linear programming.
Decomposition algorithm for linear and mixed-integer linear programming.
General nonlinear programming algorithm:
- Interior point trust region method with line search.
- Active-set trust region method with line search.
- Multistart capability.
Quadratic programming with a state-of-the-art solver tailored for large-scale optimization.
Multiple network analytics and optimization algorithms:
- Network structural enumeration and descriptive analysis.
- Network flow and routing optimization.
- Matching and spanning tree algorithms.
Parallel hybrid global/local search optimization, including multiobjective optimization.
Constraint programming capabilities with scheduling and resource features.
Project and resource scheduling.
Critical path method (CPM) and CPM-based resource-constrained scheduling.
Calendars, work shifts and holidays for determining resource availability and schedules.
Full support for nonstandard precedence relationships.
Ability to include PERT estimates of duration.
Versatile reporting, customizable Gantt charts and project network diagrams.
Earned Value Management analysis for project tracking execution.
Decision analysis:
- Create, analyze and interactively modify decision tree models.
- Calculate the value of perfect information (VPI) and the value of perfect control (VPC).
Bill of material (BOM) processing:
- Read from standard product structure data files and part master files or combined files.
- Produce single- or multiple-level bills of material, including indented and summarized BOM.
- Produce summarized parts, listing items and quantities required to meet the specified plan.
For more information, see SAS/OR Software.