SIEBEL Analytics Functional Training makes a point on how to measure and evaluate business performance across customers. We provide the well-structured SIEBEL course content in an easy and understandable way.
Siebel Analytics is an enterprise to measure and evaluate business performance across customers. Siebel Analytics means a branch of Siebel dealing with Analysis, it helps in analyzing past, present and future opportunities with the help of Dashboard Reports to determine actions required to meet the sales targets. Siebel Analytics Functional Training has always been transactional application and it is very difficult to do analysis of data that is residing in Siebel.
SIEBEL ANALYTICS FUNCTIONAL TRAINING OVERVIEW
Siebel Analytics Functional training provides Repository Basics by testing and validating them. Learn to Build the Physical Layers, Business Model Layer and Presentation Layer of a repository. Further, take a note on Modeling Time series data, Slowly changing dimensions, Header and detail data, Extension tables and its leading practices.
Siebel Analytics Functional Training Curriculum
Siebel Analytics Overview
Exploring Siebel analytics User Interfaces
Repository Basics
Implementation Methodology
Building the Physical Layers of Repository
Building the Business Model Layer of a repository
Building the Presentation Layer of a repository
Testing and Validating a Repository
Adding Multiple Sources to a dimension
Adding calculations to a fact
Creating Dimensional Hierarchies and Level-Based Measures
Using Aggregates
Using Partitions of fragments
Using Repository Variables
Modeling Time series Data
Modeling Slowly Changing dimensions
Modeling Header and detail Data
Prototyping and Non-Dimensional data
Modeling Extension tables
Modeling leading practices
Analytics Security
Cache Management
Answers
Dash boards
Delivers
Administration
Introduction ETL
Data ware concepts
Creating dimension Hierarchies
Adding Multiple Sources
Customizing User Interface
Adding calculation to facts
Configuring guided Navigation Links
Administering BI Web Catalog
Using Aggregates
Using Delivers
Using partitions Fragments
Using briefing books
Using Repository Variable
Dash board design Principles best Practices
Modeling time series Data
Security
Cache Management
Multi user Development Environment
Utilities