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SAS Supply Chain Intelligence

Title Level Training Formats
SAS Field Quality Analytics: Transitioning from SAS Warranty Analysis
This course addresses SAS Field Quality Analytics, and teaches experienced users of SAS Warranty Analysis how to select product and field event data and perform analyses.

2 Fundamental Classroom
SAS Asset Performance Analytics End User Training
This course provides an overview of SAS Asset Performance Analytics and its user interface. Students create a data selection, and perform fundamental reporting. The following statistical techniques are introduced and applied: Pareto analysis, correlations, variable clustering, principal component analysis, root cause analysis, and stability monitoring.

2 Fundamental Classroom
SAS Field Quality Analytics 6.1: Essentials
This course addresses SAS Field Quality Analytics, and teaches end users how to select product and field event data and perform analyses.

2 Fundamental Classroom
SAS Demand-Driven Forecasting: Using the Solution
This course teaches forecasters and planners how to use SAS Forecast Analyst Workbench to predict product demand by using complex statistical models, develop a forecast consensus across the organization, and aggregate selected forecasts in the SAS Supply Chain Intelligence Center.

2 Fundamental Classroom
SAS Forecast Analyst Workbench 5.2 : Using the Solution
This course provides you with the knowledge and skills needed to use the Investigator User Interface, a component of SAS Fraud Framework. The course covers identifying individuals associated with fraud, researching the data related to the individuals, and exploring the social network of individuals. This course requires customization; work with your Education Sales representative for lead time and pricing. This self-study course includes structured course notes that provide a detailed overview, essential skills, and exercises, along with a software Virtual Lab to practice.

What’s Included with Your e-Learning?

  • digital course notes for self-study
  • Virtual Lab: 30 hours of hands-on software practice

  • 2 Fundamental Classroom e-Learning
    SAS Collaborative Planning Workbench 5.2: Using the Solution
    This course teaches you how to use SAS Collaborative Planning Workbench to develop a consensus forecast across your organization. This self-study course includes structured course notes that provide a detailed overview, essential skills, and exercises, along with a software Virtual Lab to practice.

    What’s Included with Your e-Learning?

  • digital course notes for self-study
  • Virtual Lab: 30 hours of hands-on software practice

  • 2 Fundamental Classroom e-Learning
    SAS Demand-Driven Planning and Optimization 5.2: Solution Orientation
    The Solution Orientation training prepares members of your organization's project team to effectively implement the SAS Demand-Driven Planning and Optimization solution. This course teaches you key concepts, terminology, and base functionality integral to the SAS Demand-Driven Planning and Optimization solution. After completing the course, participants will be prepared to engage in the upcoming requirements-gathering sessions. This self-study course includes structured course notes that provide a detailed overview, essential skills, and exercises, along with a software Virtual Lab to practice.

    The e-learning includes:

    • digital course notes for self-study
    • Virtual Lab: 30 hours of hands-on software practice

    2 Fundamental Classroom e-Learning
    SAS Field Quality Analytics: Advanced Topics
    This course addresses SAS Field Quality Analytics. The course teaches power users of the solution how to configure advanced analysis settings and to perform and interpret advanced and early warning analysis.

    3 Intermediate Classroom
    Using SAS Inventory Optimization Workbench 5.2
    At the conclusion of this course, students will be able to explain how using the features and functions of SAS Inventory Optimization Workbench 5.2 will enhance their ability to calculate optimal inventory replenishment policies based on user-specified constraints thus enabling them to maintain customer service levels while minimizing average total costs.

    3 Intermediate Classroom