BOXI R3 ARCHITECTURE PDF

Are you new to the business sector? Do you want to upgrade your skills? Are you unable to grasp the business objectives? Business objective web intelligence XI 3 is a management tool which is specifically created for the business users who need to produce effective reports using this tool. This helps the learners to analyse, access and share corporate data using business objectives.

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Data warehouse:. Subject-Oriented : A data warehouse can be used to analyze a particular subject area. Integrated : A data warehouse integrates data from multiple data sources. For example, source A and source B may have different ways of identifying a product, but in a data warehouse, there will be only a single way of identifying a product. Time-Variant : Historical data is kept in a data warehouse. For example, one can retrieve data from 3 months, 6 months, 12 months, or even older data from a data warehouse.

This contrasts with a transactions system, where often only the most recent data is kept. For example, a transaction system may hold the most recent address of a customer, where a data warehouse can hold all addresses associated with a customer.

Non-volatile : Once data is in the data warehouse, it will not change. So, historical data in a data warehouse should never be altered. Different data warehousing systems have different structures. Some may have an ODS operational data store , while some may have multiple data marts. Some may have a small number of data sources, while some may have dozens of data sources. In view of this, it is far more reasonable to present the different layers of data warehouse architecture rather than discussing the specifics of any one system.

In general, all data warehouse systems have the following layers:. The picture below shows the relationships among the different components of the data warehouse architecture. Data Source Layer. This represents the different data sources that feed data into the data warehouse.

The data source can be of any format — plain text file, relational database, other types of database, Excel file, … can all act as a data source. Many different types of data can be a data source:. All these data sources together form the Data Source Layer.

Data Extraction Layer. Data gets pulled from the data source into the data warehouse system. There is likely some minimal data cleansing, but there is unlikely any major data transformation. Staging Area. ETL Layer. This layer is also where data cleansing happens.

Data Storage Layer. This is where the transformed and cleansed data sit. Based on scope and functionality, 3 types of entities can be found here: data warehouse, data mart, and operational data store ODS. In any given system, you may have just one of the three, two of the three, or all three types.

Data Logic Layer. This is where business rules are stored. Business rules stored here do not affect the underlying data transformation rules, but does affect what the report looks like. Data Presentation Layer. This refers to the information that reaches the users. OLAP tools are geared towards slicing and dicing of the data.

As such, they require a strong metadata layer, as well as front-end flexibility. Popular Reporting Tools. Business Objects :. What is Business Objects?

The suite includes the following key applications. Data Sources that Business Objects can connect:. Different versions are in Business Objects:. Business Objects 5. Business Objects 6. Business Objects XI. Crystal Reports and. Business Objects 3. Client Tire:. The client tier is the only part of the Business Objects Enterprise system that administrators and end users interact with directly.

This tier is made up of the applications that enable people to administer, publish, and view reports and other objects. Application Tire:.

The application tier hosts the server-side components that process requests from the client tier as well as the components that communicate these requests to the appropriate server in the intelligence tier. Intellegence Tire:. The intelligence tier manages the Business Objects Enterprise system. It maintains all of the security information, sends requests to the appropriate servers, manages audit information, and stores report instances. Processing Tire:. The processing tier accesses the data and generates the reports.

It is the only tier that interacts directly with the databases that contain the report data. Data Tire:. The data tier is made up of the databases that contain the data used in the reports. Business Objects Enterprise supports a wide range of corporate databases. Business Objects integration with SAP. It contains 3 domains. Security Domain:. The security domain has the user security info and other domains address.

Universe Domain:. Information about universes created and exported. Document Domain:. Contains information about scripts or stored procedures, text files. A universe is a semantic layer that maps the data structure found in databases tables, columns, etc.

A universe can represent any specific business area, process, or department. For example, a universe can relate to a department in a company such as marketing or accounting.

Universe can be created through universe designer:. It auto-generates the Structured Query Language that interrogates the database tables so that business users do not need to understand this language or even know that it exists. You can combine the SAP data with your relational data e.

Teradata by synchronization within Web Intelligence. Note: If the universe has designed on top of the SAP Bex query you will not find the table structure in the structure pane. Creation of the Universe on top of the BEX query step by step :. Connection types:. There are three different types of connections. Note: Here since we are distributing the universe in to repository will go for secured connection. Note: If the server is responding then the given credentials of the SAP BI system is working else need to connect the other system.

Then you can see the structure of the newly created universe. After Save the Universe need to export it into repository. Repository infromation is not correct as of XI version and relates only to 5. There are no more Domains. The Tier structure is not entirely correct either. Former Member. Posted on August 7, 11 minute read. Follow RSS feed Like. In general, all data warehouse systems have the following layers: The picture below shows the relationships among the different components of the data warehouse architecture Data Source Layer This represents the different data sources that feed data into the data warehouse.

Many different types of data can be a data source: Operations — such as sales data, HR data, product data, inventory data, marketing data, systems data Web server logs with user browsing data. Internal market research data. Third-party data, such as census data, demographics data, or survey data.

Data Extraction Layer Data gets pulled from the data source into the data warehouse system. Data Storage Layer This is where the transformed and cleansed data sit.

Data Logic Layer This is where business rules are stored.

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Data warehouse:. Subject-Oriented : A data warehouse can be used to analyze a particular subject area. Integrated : A data warehouse integrates data from multiple data sources. For example, source A and source B may have different ways of identifying a product, but in a data warehouse, there will be only a single way of identifying a product. Time-Variant : Historical data is kept in a data warehouse.

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This Blog is to share my knowledge on Business objects. This is a Business objects Mashup will have all the article on Business objects. Hello Mareswar This is very informative. Where can I find some more information with figures?! Also, if you have any useful information on migrating the universes and reports to XI, could you please forward to my email swapna. This is very informative. Emai ID: pswarna1 gmail.

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