SAP has a 3 tier architecture based on R/3, 3 tiers namely Presentation Server, Application Server, Database Server. Basically, sapgui.exe is a program as presentation server it is installed on the user workstation. What you will learn in this part is:Introduction to SAP then its  SAP architecture, understanding the SAP Business Intelligence and Business Warehouse, an overview of SAP Business Warehousing Works, the description of Business Warehousing works model, understanding Persistent Staging Area data sources, data transfer process, Char and Key Figure Model.

The most interesting part is the data warehouse is front end where the user gets its data on an online analytical tool or data mining tool. But at the same time, we cannot ignore a lot of what is going on in the back end to bring this reliable and clean data to the user. This part will broaden understanding of the data warehousing module, reporting and ETL, introduction to data warehousing workbench, concepts, and description.

SAP modeling helps to create an information view, it also creates a multidimensional data model, different type of attributes are used in modeling that we will learn about in this part of the tutorial apart from that we will also learn SAP business warehouse data modelling, learning about SAP Source and Non SAP Source, understanding the source system, persistent staging area Info Providers like info, char, cubes, do modelling.

The task of a transformer is to transfer data from a particular source format to a target format in data warehouse layer while the scheduler is used mainly for load process of defining parameters for data transfer of a particular data source. Therefore it is important to Learn about the SAP Business Warehousing Data Transformation, and Scheduler, how to extract data from flat files to SAP business warehouse, you will also learn about the differences between internal and external sources, how to change data sources, create and working with metadata of target, editing info object catalog, creating of company application, and working with Scheduler.

Live demo to extract data from flat files to SAP business warehouse then hands-on too on changing data sources, editing info object catalogue, creating and working with metadata of the target, creating company application, deploy a scheduler.

Data schema tells about the logical configuration of all part of a relational database there are different types of schema namely classical data schema (others schema: Extended Star Schema) which is multidimensional data model based on fact table. This part will deepen your Understanding of SAP architecture via SAP BI/Business Warehousing data schema, learning about Extended Star Schema, understanding Master Data Table, master data load, attribution of master data, hierarchies and text of master data.

Info-Providers have very different characteristic values still every BW-infoprovider provides data for every query. So this part will be all about: what is an SAP BW info provider, Introduction to data store object, How to design and work with standard data store object, Edit and display data store object, Loading of data in DSO as an info provider, Displaying and changing transformation in DSO.

Hands-on Exercise – everyone will be assisted to Design and work with standard data store object, how to edit and display data store object, loading data in DSO as an info provider, displaying and changing transformation in DSO

A data store serves as a storage location for aggregated and cleansed data.

There are 3 types of data store object i.e. Standard data store object, direct data store object, write optimized data store object. This module explains about direct data store object, functionalities of DSO, its advantages, drawbacks, and creation of Datastore object.

A data store serves as a storage location for aggregated and cleansed data. Write optimized data store object is one of the 3 data store types which will be discussed in this part of the tutorial. The Data in DSO is stored in a transparent and flat database tables. Write-optimized data store objects, learning to create write-optimized data store objects, the basic characteristics and rules concepts are explained in this module.

The Infoproviders provide data for every query. Infoset is special kind of infoprovider it does not store data physically although it logically joins data and provide that data for BI query, it also describes the data source which is defined as a rule of join on datastore objects. The learner will be Introduced to Infoset, the rules of Infoset, deployment of Infoset for data modeling, a specific kind of Info providers, the Join Concept and application of Infoset.

Infocube is also an area or data storage area in which physically extracted data from source system are stored. It is also described as a self-contained dataset. This part will make you understand the multidimensional data structure, creating a standard info cube, there are various types of info cubes, important rules for designing an info cube, main characteristics and key features, understanding Star Schema, Extended Star Schema and fact tables.

Multi-provider is built on basic infocubes, infosets etc. A multi-provider queries uses union, while Infoset uses join. Multi-provider is working as union operator and brings all records irrespective of the target for the given selection.  Infoset is used to bring data which are common in the infoproviders.  Both are structures. This module will help the learner to understand the concept of Multi-provider, rules of updating, combining data from various info providers, learn about Virtual and Hybrid providers.

The learner will also learn on how to work with virtual and hybrid providers, combine data from various info providers, setting the rules of updating, work with virtual and hybrid providers.