Validates the skills required to build reports, analyses, and dashboards for consumption by business users. Successful candidates should be skilled in topics such as:

  • information consumer reporting applications
  • data management
  • creating Information Maps
  • building a SAS BI Dashboard application
  • building stored processes
  • utilizing multidimensional (OLAP) data sources.

For those who have the skills and knowledge necessary for the administration of the platform for SAS Business Analytics. Successful candidates should be able to:

  • secure the SAS configuration on each server machine
  • check status and operate servers
  • monitor server activity and administer logging
  • establish formal, regularly scheduled backup processes
  • add users and manage their access
  • establish connectivity to data sources
  • set up and secure metadata folder structures
  • administer repositories and move metadata.

Tests the candidate's ability to apply the skills and knowledge necessary for Data Integration Development in the SAS environment. Successful candidates should be skilled in tasks such as:

  • defining architecture of the platform for SAS Business Analytics
  • creating metadata for source and target data
  • creating metadata for target data and jobs
  • working with transformations
  • working with tables and table loader transformation
  • working with slowly changing dimensions
  • defining generated transformations
  • deploying jobs.

Designed for SAS Enterprise Miner users who perform predictive analytics. During this performance-based examination, candidates will use SAS Enterprise Miner to perform the examination tasks. It is essential that the candidate have a firm understanding and mastery of the functionalities for predictive modeling available in SAS Enterprise Miner. Successful candidates should have the ability to:

  • prepare data
  • build predictive models
  • assess models
  • score new data sets
  • implement models.

Designed for analysts who are using SAS Visual Analytics to explore data and create reports that provide concise, interactive, and relevant data summaries. Successful candidates should be skilled in topics such as:

  • adding and manipulating data items within SAS Visual Analytics
  • exploring data with SAS Visual Analytics Explorer
  • creating report content using SAS Visual Analytics Designer

The ideal certification for those relatively new to SAS programming or new to SAS certification. Successful candidates should have experience in programming and data management using SAS 9 and should be able to:

  • import and export raw data files
  • manipulate and transform data
  • combine SAS data sets
  • create basic detail and summary reports using SAS procedures
  • identify and correct data, syntax and programming logic errors.

Designed for SAS professionals who use SAS/STAT software to conduct and interpret complex statistical data analysis. Successful candidates should have experience in:

  • analysis of variance
  • linear and logistic regression
  • preparing inputs for predictive models
  • measuring model performance.

Validates a candidates' ability to apply SAS programming skills to clinical trials data. Successful candidates should have experience in:

  • clinical trials process
  • accessing, managing, and transforming clinical trials data
  • statistical procedures and macro programming
  • reporting clinical trials results
  • validating clinical trial data reporting.

Represents the upper echelon of SAS programmers who demonstrate a high level of proficiency in SAS programming expertise. Successful candidates should be skilled in tasks such as:

  • using advanced DATA step programming statements and efficiency techniques to solve complex problems
  • writing and interpreting SAS SQL code
  • creating and using the SAS MACRO facility.

Designed for individuals who are using DataFlux Data Management Studio to perform a variety of data quality tasks including profiling data, cleansing data and monitoring data for usability. Successful candidates should be able to:

  • create and review data explorations and data profiles
  • create data jobs for data improvement
  • parameterize jobs and business rules within DataFlux Data Management Studio
  • create, maintain and apply business rules and tasks
  • understand the QKB components and various definition types
  • apply QKB components to address data quality issues
  • expand basic functionalities using Expression Engine Language (EEL)
  • use macro variables
  • create process jobs
  • configure the Data Management Server to run jobs.