Course announcements

  • This freshly updated course will provide you with the skills to take advantage of the significant improvements and new capabilities of SAP Predictive Analytics.

Goals

  • This course will prepare you to:
  • Understand predictive analytics concepts and approaches, as well as how they are implemented within the context of the SAP Predictive Analytics tool.
  • Develop the ability to use Predictive Analytics within a Data Science project context.
  • Be able to use automated analytics capabilities to build, score and implement classification, regression and time-series models.
  • Use Data Manager to prepare and manipulate data to support modelling.
  • Understand and implement Predictive Factory to import, build and schedule models.
  • Build Social and Recommendation models
  • Introduction to Expert Analytics and the Predictive Analytics Library (PAL)

Audience

  • Application Consultant
  • Business Analyst
  • Program / Project Manager
  • System Administrator
  • Technology Consultant

Prerequisites

Essential

  • None

Recommended

  • Basic statistical skills and a background in Business Analytics and Data Modelling

Course based on software release

  • SAP Predictive Analytics 3.3

Content

  • Introduction to Predictive Analytics
  • Welcome introduction and agenda
  • Introduction to Predictive Analytics
  • Describing Predictive Analytics
  • Describing SAP Predictive Analytics
  • Outlining Predictive Analytics Project Frameworks
  • Detailing SAP Analytics Use Case examples
  • Foundations of Automated Analytics (1)
  • Explaining SAP Predictive Analytics Data Types and Storage
  • Defining Automated Data Encoding Fundamentals
  • Describing Model Building in SAP Predictive Analytics
  • Predictive Factory
  • Describing Predictive Factory
  • Listing the SAP Predictive Factory Roles
  • Describing the SAP Predictive Factory Server Setup
  • Checking Data Descriptions
  • Building a Time Series Model in SAP Predictive Factory
  • Explaining Segmented Time Series Modeling
  • Describing Classification Models
  • Building a Classification Model in SAP Predictive Factory
  • Explaining Classification Model Output
  • Interpreting the Error Matrix
  • Applying a Classification Model
  • Creating and Scheduling Tasks
  • Explaining Regression Modeling in SAP Predictive Factory
  • Building a Regression Model
  • Describing Deviation Analysis
  • Importing Models from SAP Predictive Analytics into Predictive Factory
  • Data Manager
  • Explaining Data Preparation
  • Outlining Data Manipulation in SAP Predictive Anaytics
  • Outlining Data Manager
  • Using Data Manager and Toolkit
  • Classification Modeling with Modeler
  • Building a Classification Model with Modeler
  • Explaining the Confusion Matrix
  • Applying a Model
  • Performing Deviation Analysis in Modeler
  • Outlining Advanced Functionality
  • Advanced Data Description Functionality
  • Regression Modeling with Modeler
  • Training a Regression Model
  • Explaining Regression Model Output
  • Improving Regression Model Performance
  • Applying a Regression Model
  • Clustering with Automated Analytics
  • Explaining Clustering and Segmentation
  • Describing Supervised and Unsupervised Clustering
  • Explaining Cluster Range
  • Explaining Cluster Model Outputs
  • Applying the Cluster Model
  • Building a Cluster Model in SAP Predictive Analytics
  • Time Series with Modeler
  • Building aTime Series Model with Modeler
  • Social and Recommendation
  • Building a Social Network (link) Model using Telco CDR Data
  • Building a Product Recommendation Model using Link Analysis
  • Foundations of Automated Analytics (2)
  • Outlining Data Partition Strategies in SAP Predictive Analytics
  • Explaining the Foundations of Automated Modeling
  • Describing the Data Encoding Process
  • Advanced Model Curves
  • Final Exercise
  • SAP Creating a Retail Analysis