SAS Analytics Pro and
SAS Analytics Pro Advanced Programming Features Lists

Explore the Features of SAS Analytics Pro

Easily accessible browser-based development environment (SAS Studio)

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 (SAS/STAT)

Advanced statistical analysis — SAS/STAT

  • 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 (SAS/GRAPH)

Data visualization, presentation & delivery — SAS/GRAPH

  • 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 Software.

Protect data as it passes between platforms or over networks (SAS/SECURE)

Protect data as it passes between platforms or over networks — (SAS/SECURE)

    Powerful data connectivity with support for SQL (Data Connectors)

    Powerful data connectivity with support for SQL — Data Connectors

    • Access to your local and/or enterprise data.
    • Ability to read data in nearly any format, from nearly any kind of file data repository.
    • Robust macro language, which reduces coding for common tasks.
    • Runs interactively or in batch mode.
    • For more information, see Data Connectors.

    Additional Capabilities Available With SAS Analytics Pro Advanced Programming

    Model, forecast & simulate business processes for improved strategic & tactical planning (SAS/ETS)

    Model, forecast & simulate business processes for improved strategic & tactical planning — SAS/ETS

    • 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 Software.

    Operations research software for identifying which actions will produce the best results, given constraints (SAS/OR)

    Operations research software for identifying which actions will produce the best results, given constraints — SAS/OR

    • 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.

    Statistical process control software for improved product & process quality (SAS/QC)

    Statistical process control software for improved product & process quality — SAS/QC

    • 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.

    Powerful, flexible matrix programming language (SAS IML)

    Powerful, flexible matrix programming language — SAS IML

    • 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.