What does Forrester say about Oracle Data Integrator (Sunopsis)?

“Sunopsis’ ability to connect a wide variety of data sources and targets will allow Oracle to address the heterogeneous data management environments its enterprise architect customers must contend with.

This acquisition could be a big win for the Siebel, PeopleSoft, and JD Edwards customers who, following the acquisitions by Oracle, find themselves smack in the middle of a perhaps unwanted Oracle-dominated ecosystem.”

Please read the entire paper here:

Sales Performance Report in SAP

I studied a sales performance reports found in SAP Sales Information System.

This report analyzes the monthly sales performance of a number of sales reporting structure.

Install Siebel Analytics – Step by Step Installtion Screenshots

Note added on Jun 21, 2007:  The  Siebel Analytcis is now called Oracle BI Applications.  The latest version is 7.9.x which can be installed on top of Oracle BI EE10.1.3.2.   Please go to the following link from Oracle to get the step by step instruction:

What does Gartner say about Oracle Data Integrator (Sunopsis)?

Sunopsis fits into Oracle’s longtime strategy of building operating-system- and hardware independent tools. Fusion Middleware customers have heterogeneous IT environments, Sunopsis have a positive influence on Fusion Middleware.

See details:

Download Oracle Data Integrator (Sunopsis) from Oracle Technology Network!

Sunopsis has now renamed as Oracle Data Integrator and the evaluation version of the software is available for download here:

What is a Conformed Dimension?

A simple answer is that a conformed dimension is a dimension that is shared across fact tables.

A conformed dimension is important because it allows queries to be executed across star schemas. This activity is also called Drill Across. When you drill across, you are adding more data from another fact table to the existing rows.

Examples of obvious conformed dimensions include Customer, Location, Organization, Time, and Product.

Learning ETL – Mapping

Column level mapping is to define the transformation rule that maps columns from the source datastore to on of the target datastore column.

Many ETL tool nowady can automatically map a column from the source to one in the target if they have the same name. Most of the ETL tool also allow you to drag and drop column from the source to the target to define the mapping.

Here are some types of mapping:

Learning ETL – Architecture

The central component of any ETL tool is the repository. It typically stores the metadta for all applications, including both source and target systems. It also contains the business logic about mapping and transforming the data from one to the other.

How does Oracle BI Enterprise Edition support Slowly Changing Dimensions (SCDs)?

You need to handle the SCD in your data warehouse schema design. The technique you use will probably affect your ETL process startegy. It will also affect how the BI tool querying your data.

OBIEE is not a ETL tool. It provides the tool, DAC – Data Warehouse Administation Console for managing and monitoring the ETL processes, but its focus is really on the logical data modeling and data access. You need to define how a fact table and a dimension table are joined in OBIEE.

How to handle Slowly Changing Dimensions (SCDs) in data model design?

There are multiple methods to handle the slowly changing dimensions. Which technique to use depends on your business requirements. The choice among these three methods are not a technical design decision since their behaviors are different.

Type One: Overwite the old data with new data

Using this method, you do not store the histoy. For example, that say each customer can

What are slowly changing dimensions?

Slowly changing dimensions are used to describe the date effectivity of the data. It describe the dimensions whose attribute value vary over time.

This term is commonly used in the Data Warehousing world. However, the problem exists in the OLTP, relational data modeling as well.

Example:

The sales representative assigned to a customer may change over time. Linda was the salesrep for ABC, inc. before March last year. Kathy later becomes the representative for this account.

You may want to track the data “as is”, “as was”, or both. If you show the year total sales, you can either report as the sales are all generated by Kathy, or actually break the number down between Linda and Kathy.

Where can I get the Oracle BI Enterprise Edition for evaulation?

Oracle have made its Oracle Business Intelligence Enterprise Edition (OBIEE) available for evaluation. I just followed the following steps to install it on my laptop.

Why do I need to use DAC from Oracle BI?

Data Warehouse Application Console (DAC) works together with Informatica to acomplish the ETL for pre-packaged BI applications.

Here are what happen behind the scene:

History of Data Warehouse

In the early stages only two vendors within the IT industry foresee what was happening later become data warehouse.  One was Teradata Corporation, which originated the database machine that could handle a terabye of data.  It was the first industry -hardened massively parallel computer. Teradata became at least for five years in succession one of the fast growing company at that time.

The second vendor was IBM which published “Information Warehouse” framework as early as 1987.

Data Warehousing then became the key trend in corporate computing in the 1990s.  Data warehousing is not really a technology trend per se.  It was primarily driven by the business envirobment.

Learning ETL – ETL Process

ETL Process

Here is the typical ETL Process:

• Specify metadata for sources, such as tables in an operational system
• Specify metadata for targets—the tables and other data stores in a data warehouse
• Specify how data is extracted, transformed, and loaded from sources to targets
• Schedule and execute the processes
• Monitor the execution

A ETL tool thus involves the following components:

• A design tool for building the mapping and the process flows
• A monitor tool for executing and monitoring the process

The process flows are sequences of steps for the extraction, transformation, and loading of data. The data is extracted from sources (inputs to an operation) and loaded into a set of targets (outputs of an operation) that make up a data warehouse or a data mart.