**Level:**

*Introduction & Overview*

**Languages:**

*English*

**Course included in the following training paths:**

*SAP Predictive Analytics*

## 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