Dylan’s BI Study Notes

My notes about Business Intelligence, Data Warehousing, OLAP, and Master Data Management

  • About me

    I am a senior development manager working for Oracle BI Applications development. My job involves the common area, including data warehouse modeling and dimension conformance. I was involved in Oracle E-Business Suite Financial Architecture, Oracle Customer Hub, and Oracle Fusion Projects product development in the past. Disclaimer: Opinions expressed in this blog are entirely my own and do not reflect the position of Oracle.
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Archive for April, 2007

An evaluation of Oracle BI Enterprise Edition from Intelligent Enterprise

Posted by Dylan Wan on April 24, 2007

A good article from Intelligent Enterprise about the Oracle BI Enterprise Edition - Put to the test: Oracle BI Enterprise Edition.

Here is the part I feel worth highlight: Read the rest of this entry »

Posted in BI, BI Links, Business Intelligence, OBIEE, Oracle, Oracle BI Suite EE, Siebel Analytics | 1 Comment »

Added my blog to Technorati

Posted by Dylan Wan on April 21, 2007

Posted in Business Intelligence | No Comments »

Aggregation for Data Warehouse, Part 2

Posted by Dylan Wan on April 9, 2007

In the aggregation for Data Warehouse, Part 1, I mentioned that there are multiple ways to do the aggregation for data warehouse. One of the method is to use the ETL tool to maintain the aggregated tables. Read the rest of this entry »

Posted in BI, Data Warehouse, ETL, Infomatica, OWB, Oracle Data Integrator, Sunopsis | No Comments »

Aggregation for Data Warehouse, Part I

Posted by Dylan Wan on April 4, 2007

A data warehouse typically contains historical data that are viewed in a summary form and then let the users to drill down to the more detail transactions. The fact data can easily reach the size of gigabytes to terabytes. Summarizing the huge volume of the fact data online may not be practical.

One of the techniques employed by data warehouse designers to improve performance is the creation of summaries, or aggregated tables, which contains pre-calculated data.

For example, you may see the costs against your project with a inception to date amount, which include the historical cost charged against the project up to the current date. Without the pre-calculated data, a query to fetch the ITD amount may take minutes to fetch and summarize the fact data. Using an aggregated table, the amount is periodically refreshed with the amounts from the recent transactions in the latest summarization process. Fetching the data online from the aggregated table probably takes only seconds.

There are multiple ways to create such aggregations: Read the rest of this entry »

Posted in AW, BI, Business Intelligence, Data Warehouse, ETL, OLAP | No Comments »