BusinessObjects Enterprise architecture basic terminology

Host
A host can be a physical computer or virtual machine.


Server

A server is an Operating System (OS) level process hosting one or more services.
For example,
CMS and Adaptive Processing Server are servers.
A server runs under a specific OS account and has its own PID.


Service

A service is a server subsystem that provides a specific function. The service runs within the
memory space of its server under the Process ID (PID) of the parent container (server).
For example,
the Web Intelligence Scheduling and Publishing Service is a subsystem running within the Adaptive Job Server.


Node


A node is a collection of BusinessObjects Enterprise servers, all running on the same host.
One or more nodes can be on a single host. Each node is managed by a Server Intelligence Agent (SIA).


Server Intelligence Agent


The SIA is a locally run service managed by the operating system. The task of the Server
Intelligence Agent (SIA) is to start, stop, and monitor locally run BusinessObjects servers.

When one of the managed servers goes down unexpectedly, the SIA restarts the server immediately.
When you issue a command in the CMC to stop a server, the SIA stops the server.

When you create a SIA, you create a new node. A node is a collection of BusinessObjects
Enterprise servers which run on the same host and are managed by a single SIA.

You can add servers to the node and you can have more than one node on the same machine.

The SIA continuously monitors server status information, which is stored in the CMS databases.

When you change a server's settings or add a new server in the CMC, the CMS notifies the SIA
and the SIA performs the jobs accordingly.


................ continue..next we will discuss about Workflows for each servers and how the communicate each server

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Inmon vs. Kimball - An Analysis

Mr. William (Bill) Inmon is known as the “Father of Data Warehousing”, entitled for coining the term “Data Warehouse” in 1991. He defined a model to support “single version of the truth” and championed the concept for more than a decade. He also created “Corporate Information Factory” in collaboration with Ms. Claudia Imhoff. Mr. Inmon is known to have published 40+ books and 600+ articles.

Mr. Ralph Kimball is known as the “Father of Business Intelligence” for defining the concept behind “Data Marts”, for developing the science behind the analytical tools that utilize dimensional hierarchies, and for conceptualizing star-schemas and snowflake data structures. He defined a model to support analytical analysis and championed data marts for more than a decade. Though Kimball’s writings do not exceed Inmon’s by quantity, Kimball’s books are all-time best sellers on data warehousing.

Inmon and Kimball are two pioneers that started different philosophies for enterprise-wide information gathering, information management, and analytics for decision support. Inmon believes in creating a single enterprise-wide data warehouse for achieving an overall business intelligence system. Kimball believes in creating several smaller data marts for achieving department-level analysis and reporting.

APPROACHES
Inmon’s philosophy recommends to start with building a large centralized enterprise-wide data warehouse, followed by several satellite databases to serve the analytical needs of departments (later known as “data marts”). Hence, his approach has received the “Top Down” title.

Kimball’s philosophy recommends to start with building several data marts that serve the analytical needs of departments, followed by “virtually” integrating these data marts for consistency through an Information Bus. Hence, his approach received the “Bottom Up” title. Mr. Kimball believes in various data marts that store information in dimensional models to quickly address the needs of various departments and various areas of the enterprise data.

STRUCTURES
Besides the differences in approaches, Inmon and Kimball also differ in the structure of the data. Inmon believes in creating a relational-model (third normal form: 3NF) where as Kimball believes in creating a multi-dimension model (star-schema and snowflakes).

Inmon argues that once the data is in a relational model, it will attain the enterprise-wide consistency which makes it easier to spawn-off the data-marts in dimensional-models. Kimball argues that the actual users can understand, analyze, aggregate, and explore data-inconsistencies in an easier manner if the data is structured in a dimensional-model. Additionally, to enable the Information Bus, data marts are categorized [Imhoff, Mastering Data warehouse design] as atomic data marts, and aggregated data marts that both use dimensional-models.

Irrespective of the structural differences in the model, both Inmon and Kimball agrees that there is a need to separate the detailed-level data from aggregated-level data.

CONTENT
Another difference is in the granularity of the content. Inmon believes that the content in the data warehouse has to be at the most granular level possible and must include all the possible historical data within an enterprise. His argument is that the end-users will mandate the needs on the level of data-detail that are not known at the time of building the data warehouse.

COMMON GOALS
Though Mr. Inmon and Mr. Kimball have different philosophies to their approach, they do tend to agree with each other in an indirect manner. Though Inmon’s basis is on a single data warehouse, he stressed on iterative approach and discouraged the “big bang” approach. On the other hand, though Kimball’s philosophy is to quickly create few successful data marts at a time, he stresses on integration for consistency via an Information Bus.

DATA WAREHOUSE vs. BUSINESS INTELLIGENCE
Business Intelligence = Inmon’s Corporate Data Warehouse + Kimball’s Data Marts + Data Mining + Unstructured Data.

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